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Thread: Wanting People to Be Your Dual

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    Quote Originally Posted by Stray Cat View Post
    Do you mean the socionics evidence every member of this site continually gets but too lazy to get yourself? It must be pretty easy to draw up statistics from a website, statistics somebody else researched, statistics you claim are legitimate simply because you say they are

    Every person on this forum: "I've seen a particular socionics type use a particular socionics function quite a few things times"

    Subteigh:. "Socionics has no evidence. Big Five does. Here's a spreadsheet and a Q & A from a random website that proves it. I don't make the careful observations myself but since Big Five gives me good feels I'll believe it anyway."
    I have previously made statistics of self-typings on this forum, but I'm not in the position to attempt anything on the same scale again.

    With no standardised Socionics test instrument and only subjective opinions of third parties there simply isn't the capability to do anything scientific from a Socionics perspective within the limits of this forum.

    I have had a long and continued interest in psychology research they I often post here in the hope that it could have some significance for possible future Socionics research.

    I am not a psychologist. Wanting to be scientific about Socionics and not wanting to make unfounded statements should not mean I receive insults, or be called a -type or whatever. Stick to the facts.

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    What's the purpose of SEI? Tallmo's Avatar
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    Quote Originally Posted by Subteigh View Post
    It would be better to joke based on evidence than to be serious based on no evidence.
    Ok, but you can't translate functions into behaviour like that, so your "evidence" says nothing about types. There is no strong link between Si and health for example, or Si polr and bad health. It's just a keyword trying to grasp the fact that Si monitors inner body phenomena.
    The decisive thing is not the reality of the object, but the reality of the subjective factor, i.e. the primordial images, which in their totality represent a psychic mirror-world. It is a mirror, however, with the peculiar capacity of representing the present contents of consciousness not in their known and customary form but in a certain sense sub specie aeternitatis, somewhat as a million-year old consciousness might see them.

    (Jung on Si)

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    Quote Originally Posted by Tallmo View Post
    Ok, but you can't translate functions into behaviour like that, so your "evidence" says nothing about types. There is no strong link between Si and health for example, or Si polr and bad health. It's just a keyword trying to grasp the fact that Si monitors inner body phenomena.
    OK, but I think the evidence against is stronger than for.

    The concept of duality is surely central to Socionics, but I'm not aware of any convincing evidence in psychology that would support it.

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    Quote Originally Posted by Subteigh View Post
    I have previously made statistics of self-typings on this forum, but I'm not in the position to attempt anything on the same scale again.

    With no standardised Socionics test instrument and only subjective opinions of third parties there simply isn't the capability to do anything scientific from a Socionics perspective within the limits of this forum.

    I have had a long and continued interest in psychology research they I often post here in the hope that it could have some significance for possible future Socionics research.

    I am not a psychologist. Wanting to be scientific about Socionics and not wanting to make unfounded statements should not mean I receive insults, or be called a -type or whatever. Stick to the facts.
    The same person who claims EIEs do not use Se or Ti is pretty much the same ExI who's using Te right now

    Nobody has asked you to engage a third party. You're unwilling to test the theories yourself and, instead insist that the tests you've chosen are factual when they're really just anecdotal
    Quote Originally Posted by Subteigh View Post
    OK, but I think the evidence against is stronger than for.

    The concept of duality is surely central to Socionics, but I'm not aware of any convincing evidence in psychology that would support it.
    Convincing to everyone else or just you?

    You just said, "I am not a psychologist" yet you're looking for convincing evidence within the realm of psychology. If anything, you've convinced everyone else that even if you did get convincing evidence that you either wouldn't believe it or even be able (or want) to comprehend it

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    "Wanting People to Be Your Dual"->Argument between conflictors about the validity of Socionics.

    Fascinating.

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    Quote Originally Posted by Subteigh View Post
    It would be better to joke based on evidence than to be serious based on no evidence.
    There is no evidence though? All these correlations, negative and positive, are negligible, meaning there is no relationship. That is an official term btw. See the following table for reference. Am I missing something?

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    Psychology BSc and statistics MSc Armitage's Avatar
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    In a follow-up study one could inspect the relationship between neuroticism and general health closer by using a larger sample size, since it approaches a substantial correlation. This seems especially possible since the literature has previously observed the influence of neuroticism on physical health via its impact on mental health. But it's clear that all the other correlations do not qualify for further inspection. Overall these data seem to imply a lack of relationship between the Big Five Personality factors, perhaps with exclusion of a limited correlation between Neuroticism and general health.

    Since Subteigh pointed out himself that in Subteigh's interpretation of Socionics neuroticism is not represented, this rejects any indirect relationship between Socionics and general health being present via the Big Five Personality factors. This in turn makes the claim that XIEs would possess strong Si mood, if one already ignores the construct problem that Si and general health are not one and the same.

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    I want to point something here - for everyone -.
    When you want to use correlations, you can't just drop the number like that because a correlation of 0,2 on 10 points isn't the same as a correlation of 0,2 on 100 000 points.
    We need significativity to analyse it properly. Or at least, the number of occurrences in the study.

    Besides, jungian functions aren't a "real" things. It's a reading grid. There is no such things as "Fe likes everyone" or "Si is healthy behavior". Many SLI had poor health and are Si-leading for instance... It's a really simplistic and misleading approach to jungian functions. I can understand that people who discover jungian typology (MBTI, Socionics...) use those shortcuts but in the end it doesn't work like that.

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    Quote Originally Posted by Stray Cat View Post
    The same person who claims EIEs do not use Se or Ti is pretty much the same ExI who's using Te right now

    Nobody has asked you to engage a third party. You're unwilling to test the theories yourself and, instead insist that the tests you've chosen are factual when they're really just anecdotal
    Your're entitled to your conjectures, but are they based in evidence?

    Quote Originally Posted by Stray Cat View Post
    Convincing to everyone else or just you?

    You just said, "I am not a psychologist" yet you're looking for convincing evidence within the realm of psychology. If anything, you've convinced everyone else that even if you did get convincing evidence that you either wouldn't believe it or even be able (or want) to comprehend it
    Well, you haven't produced any evidence that supports Socionics. There is a lot of reasons why psychologists consider the MBTI of no value and I think their criticisms will be true of Socionics. They see no evidence that discrete personality types exist.

    To some extent I don't need to be a psychologist in order to interpret evidence, but it would be beneficial to be trained as one in order to not only be skilled enough to caring out research but to be in a position to carry out sizable experiments.

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    Quote Originally Posted by Ryan View Post
    There is no evidence though? All these correlations, negative and positive, are negligible, meaning there is no relationship. That is an official term btw. See the following table for reference. Am I missing something?
    Even a negligible correlation against would be strong evidence for me to think there is no evidence FOR.

    But other studies give me that impression also (e.g. that low conscientiousness individuals do not have as good health outcomes).

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    Quote Originally Posted by Subteigh View Post
    Your're entitled to your conjectures, but are they based in evidence?



    Well, you haven't produced any evidence that supports Socionics. There is a lot of reasons why psychologists consider the MBTI of no value and I think their criticisms will be true of Socionics. They see no evidence that discrete personality types exist.

    To some extent I don't need to be a psychologist in order to interpret evidence, but it would be beneficial to be trained as one in order to not only be skilled enough to caring out research but to be in a position to carry out sizable experiments.
    The evidence is the observations you make yourself. Isaac Newton made observations himself and the scientific community decided to use his evidence as the basis for certain laws. The problem is you want evidence to have "standardization" before you'll readily accept it, which is Te speak for not being able to draw analogies on your own.

    The statistics you've claimed as evidence could simply be of a preselected sample size based on conjecture. For example, if I asked people who worked at Burger King, "Would you say that you're an honest person?". Most would reply, "Yes" and be lying, not because of social pressure but because people are, generally, not accurate judges of their own character. Furthermore, there is always nuance to the human psych that the self isn't aware of and couldn't possibly admit to on one of your "standardized" tests.

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    Quote Originally Posted by Stray Cat View Post
    The evidence is the observations you make yourself. Isaac Newton made observations himself and the scientific community decided to use his evidence as the basis for certain laws. The problem you want evidence to have "standardization" before you'll readily accept it, which is Te speak for not being able to draw analogies on your own.

    The statistics you've claimed as evidence could simply be of a preselected sample size based on conjecture. For example, if I asked people who worked at Burger King, "Would you say that you're an honest person?". Most would reply, "Yes" and be lying, not because of social pressure but because people are, generally, not accurate judges of their own character. Furthermore, there is nuance to the human psych that the self isn't aware of and couldn't possibly admit to on one of your "standardized" tests.
    Ok, but you have the study I gave, which involved 8,000+ people with a standardized test, vs. your observations of Socionics types which has no standardised test and where you seem invested in Socionics tenets and not an independent observer.

    Hypotheses are based on observation, conjectures aren't necessarily. I don't think Socionics qualifies as a hypothesis.

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    Quote Originally Posted by Subteigh View Post
    Ok, but you have the study I gave, which involved 8,000+ people with a standardized test, vs. your observations of Socionics types which has no standardised test and where you seem invested in Socionics tenets and not an independent observer.

    Hypotheses are based on observation, conjectures aren't necessarily. I don't think Socionics qualifies as a hypothesis.
    How many of those 8,000+ people are you confident were being truthful? As of matter of fact, go find a psychologist, who has credentials, and ask him to interview people for their complete honesty. What you seem to be telling me is that you're confident that an acceptable number of those people will be completely honest, simply because the psychologist has credentials

    What I am suggesting to you is that a person must be unconsciously observed to get an accurate assessment of behavior. It is why psychologist observe young people from behind a glass, why zoologists observe animals even unbeknownst to the animal itself and why employers install cameras to observe business practices.

    Human psychology cannot be standardized no matter how much you try. People lie and often have low self awareness, however, if you can observe a person's psychological behavior over a period of time you can get a much more precise view of their personality type.

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    Psychology BSc and statistics MSc Armitage's Avatar
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    Quote Originally Posted by Nicozeyo View Post
    I want to point something here - for everyone -.
    When you want to use correlations, you can't just drop the number like that because a correlation of 0,2 on 10 points isn't the same as a correlation of 0,2 on 100 000 points.
    We need significativity to analyse it properly. Or at least, the number of occurrences in the study.
    This is why in the case of neuroticism I would propose conducting a follow-up study, because the correlation is close enough to being substantial that a different and preferably larger sample may make the difference.



    Quote Originally Posted by Stray Cat View Post
    How many of those 8,000+ people are you confident were being truthful? As of matter of fact, go find a psychologist, who has credentials, and ask him to interview people for their complete honesty. What you seem to be telling me is that you're confident that an acceptable number of those people will be completely honest, simply because the psychologist has credentials

    What I am suggesting to you is that a person must be unconsciously observed to get an accurate assessment of behavior. It is why psychologist observe young people from behind a glass, why zoologists observe animals even unbeknownst to the animal itself and why employers install cameras to observe business practices.

    Human psychology cannot be standardized no matter how much you try. People lie and often have low self awareness, however, if you can observe a person's psychological behavior over a period of time you can get a much more precise view of their personality type.
    Actually, you'd be surprised about how quickly people adjust and forget about the presence of a camera even when it is pointed out to them. It allows for far more natural behaviour to be observed, than when a person physically observes the participant's behaviour. Also, in order to avoid all sorts of response biases we generally mask the purpose of a study and only debrief the participants later that we examined far different behaviours than they thought that we were looking at. That way they modify the wrong behaviours, whereas the behaviours of interest they exhibit clearly, because they believe that those will not be recorded.

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    Quote Originally Posted by Subteigh View Post
    Even a negligible correlation against would be strong evidence for me to think there is no evidence FOR.
    Burden of proof: you can't prove a negative.

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    Quote Originally Posted by Rune View Post
    Do you ever find yourself wanting people to be your dual? For example, when I'm at a social gathering, I subconsciously expect people to come to me and initiate contact (ie. I'm expecting someone to pick up my slack and be more Se). I also want people to have integrity (ie. mobilizing Fi).
    No.

    Quote Originally Posted by Rune View Post
    If so, how do you resolve the disconnect when the people you're with aren't your dual?
    I simply don't care.
    If I get on with people, I get on with them; if I don't, I don't. I don't pay attention much to anyone until someone stands out to me. I am also self-sufficient, I don't depend upon people. I confront my shortcomings. I do what needs to be done, and it's as simple as that.


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    Quote Originally Posted by Stray Cat View Post
    How many of those 8,000+ people are you confident were being truthful? As of matter of fact, go find a psychologist, who has credentials, and ask him to interview people for their complete honesty. What you seem to be telling me is that you're confident that an acceptable number of those people will be completely honest, simply because the psychologist has credentials

    What I am suggesting to you is that a person must be unconsciously observed to get an accurate assessment of behavior. It is why psychologist observe young people from behind a glass, why zoologists observe animals even unbeknownst to the animal itself and why employers install cameras to observe business practices.

    Human psychology cannot be standardized no matter how much you try. People lie and often have low self awareness, however, if you can observe a person's psychological behavior over a period of time you can get a much more precise view of their personality type.
    That's a common conundrum in psychology. Many studies do include both self-assessment and third party observation. The Big Five does have one of the highest levels of correspondence between those two assessments.

    Many studies normalise the data to adjust for individuals inclined to agree with every statement.

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    Quote Originally Posted by Rune View Post
    Burden of proof: you can't prove a negative.
    This is true. But a strong negative correlation against extroversion, conscientiousness, and openness to experience for the trait of health I would consider as possible evidence in favour of what Socionics says about PoLR types. This data not only does not show a negative correlation, it shows a weak positive correlation.

    Evidence that shows no correlation between two traits is still evidence against those traits being correlated.

    Now, it is perfectly reasonable to say there is no strong relationship between the Big Five and Socionics but this is one of many things that makes me doubt that Socionics dogma is true. One big reason is the lack of evidence in psychology for the existence of discrete types of people for the whole of humanity (rather than a few extreme individuals).

    There is quite a lot of evidence between low levels of conscientiousness and poor health. I consider that by itself to be strong evidence against the concept of PoLR.

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    Psychology BSc and statistics MSc Armitage's Avatar
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    Quote Originally Posted by Subteigh View Post
    Many studies normalise the data to adjust for individuals inclined to agree with every statement.
    Actually, that's not a reason for normalizing/standardizing the data, instead we use inverted questions to pick up on acquiescence and nay saying. So first we ask if someone agrees or disagrees with the statement "I like peanut butter." only to later in the questionnaire ask them if they agree or disagree with "Peanut butter is disgusting." If they agree with both statements, it's a case of acquiescence, if they disagree with both, then the respondent is a nay sayer. Both acquiescence and nay saying are reasons for filtering out all the answers of that respondent from the data set.


    Quote Originally Posted by Subteigh View Post
    This is true. But a strong negative correlation against extroversion, conscientiousness, and openness to experience for the trait of health I would consider as possible evidence in favour of what Socionics says about PoLR types. This data not only does not show a negative correlation, it shows a weak positive correlation.
    Yes, but in the scientific community we have agreed based on Lord Fisher, the statistician, of the past century, that any results with a probability of one in five to be caused by chance we deem significant and take seriously, whereas everything weaker with a larger probability of being caused by chance we deem nonsignificant and don't take seriously. @Subteigh, the correlations that you presented are nonsignificant, so scientists agree to not take those data seriously. That doesn't mean that they have been disproved, however, because nothing can ever be disproved in scientific terms and below I explain why so.


    Quote Originally Posted by Subteigh View Post
    Evidence that shows no correlation between two traits is still evidence against those traits being correlated.
    Like Rune tried to explain to you, you can only prove the existence of something, never the non-existence. It sounds counter-intuitive from a layman's perspective, but take for instance the teapot theory. Let's look at Mars through a telescope, we see no teapot flying around Mars. Does this disprove a teapot flying around Mars? According to the layman it does, but the scientist says: "No, not so quickly, we know that for this moment and at this location there might not be a teapot flying around Mars, but have we yet inspected the backside of Mars?" There is always an exception that can be found to enable the possibility of a flying teapot. Of course, this sounds silly, but it is not when instead of teapots we start talking about planets. In 2015 astronomists discovered an interesting gravitationall pull onto Sol, id est the sun, not as in @Sol. They also found erratic orbits of the asteroids in the Kuiper Belt. They hypothesized that this may be explained by a yet undiscovered planet circling around Sol but very far away. https://solarsystem.nasa.gov/planets...et-x/in-depth/

    Previous telescope inspections had not showed the existence of a ninth planet, so a layman would have concluded to be none there. However, scientists never accept something being disproved, they do not accept the null hypothesis, the absence of something, they only retain it as correct for now, but continue searching for exceptions. Another example was the hunt for the Higgs Boson. It had been mathematically theorized decades ago already, but all our particle accelerator experiments showed up nothing. The layman would have concluded the Higgs Boson to not exist, but the molecular scientists continued their search and eventually found it in 2012 with the use of CERN's Large Hadron Collider (LHC), because it achieved top speeds that no other particle collider could. https://www.newscientist.com/article...-to-misbehave/

    A similar issue surrounded nuclear fusion. Even though Sol and every other star is a gigantic fusion reactor, critics said that small, human-made fusion reactors would never be able to generate more energy than was put into them, due to their lack of scale. Previous attempts failed and laymen once again would have concluded the possibility of small scale fusion reactors thereby disproved, but the scientists did not and persevered! Last year we finally generated more energy out of a fusion reaction that we invested into it! https://www.sciencealert.com/for-the...ed-by-the-fuel

    All these examples show why scientists agree that something can never be disproved, even not the possibility of a teapot flying around Mars, because there always might be just that one exception or fact that we don't know of yet.


    Quote Originally Posted by Subteigh View Post
    Now, it is perfectly reasonable to say there is no strong relationship between the Big Five and Socionics but this is one of many things that makes me doubt that Socionics dogma is true. One big reason is the lack of evidence in psychology for the existence of discrete types of people for the whole of humanity (rather than a few extreme individuals).
    Indeed, personality operates more according to continuous scales, than discrete categories. But let's say we take the Big Five personality test with scales from 1 to 10. If someone has 9-10 on openness to new experiences, 5-6 on conscientiousness, 9-10 on extroversion, 3-4 on agreeableness, and 1-2 on neuroticism we call them "Adventurers". When someone attains 1-2 on O, 9-10 on C, 3-4 on E, 3-4 on A, and 3-4 on N we name them "Bureaucrats" instead. We can continue doing this, until we have exhausted all possible combinations, but in the case of 5 10-point Likert scales this would result in 3.125 results and that's when splitting the scales in ranges of 2, like 3-4 for instance. This means that either the labels won't be exhaustive, because you don't have all possible combinations, or you make even larger ranges, either way you lose information. There is thus far more information to be found when using the complete continuous scales, than the discrete categories, yet both the scale and the categorical system are equally valid, they are equally true. The scale system is just more accurate, because it contains more information.

    Socionics being a categorical system doesn't make it untrue per se, it only makes it less accurate. The truth or untruth of the system, id est its validity, instead depends on replicable experiments being done with large samples. If anyone knows if such experiments have been conducted, then it would be @Adam Strange.


    Quote Originally Posted by Subteigh View Post
    There is quite a lot of evidence between low levels of conscientiousness and poor health. I consider that by itself to be strong evidence against the concept of PoLR.
    Ice cream consumption and swiming pool visits are correlated, we both agree on that. If I am not at the swimming pool it doesn't mean that I cannot eat an ice cream, though. Nor does it mean that whenever I do eat an ice cream, I have to be at a swimming pool. The golden rule in statistics that correlation does not necessarily imply causation, but causation always implies correlation. In other words, a table is a piece of furniture ( causation always implies correlation ), but not every piece of furniture is necessarily a table (correlation does not necessarily imply causation), even if in some cases the furniture is indeed a table (correlation can at times stem from causation, but it is no guarantee).

    Low levels of conscientiousness and poor health are probably related, I might even have read an article or two about it, but it doesn't mean that if LIEs have high levels of conscientiousness they all will show to be healthy. A LIE who exercises frequently and eats healthily may still develop cancer, because its encoded in their genes without any lifestyle being able to prevent it from developing.

    Not to mention that Socionics Si relates more to being aware of one's body. I'm a LIE, I score relatively high on conscientiousness on the Big Five personality test, and am healthy (despite wanting to shed a few lockdown pounds through exercise soon). I always buy my clothes in physical stores, because I don't have the bodily awareness to get for instance the right size of shoes without the help of a knowledgeable shopkeeper. The last time I bought shoes I had been trying out a pair that I liked and was convinced that they fitted my feet well, only for the shopkeeper to point out to me that they were three sizes too large. Only when he specifically mentioned it did I realize it. Had I bought these shoes online, I would have walked for years in too large shoes without realizing it. I also tend to ignore Si matters, when I was younger I continued walking in my favourite red sneakers, even though by then they had become too small for my feet. At one point even I could no longer ignore the increasing pain I experienced from the pressure, but I think that I continued wearing them for way longer than any higher Si type would have worn them.
    Last edited by Armitage; 03-10-2022 at 07:44 PM.

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    Quote Originally Posted by Armitage View Post
    Actually, that's not a reason for normalizing/standardizing the data, instead we use inverted questions to pick up on acquiescence and nay saying. So first we ask if someone agrees or disagrees with the statement "I like peanut butter." only to later in the questionnaire ask them if they agree or disagree with "Peanut butter is disgusting." If they agree with both statements, it's a case of acquiescence, if they disagree with both, then the respondent is a nay sayer. Both acquiescence and nay saying are reasons for filtering out all the answers of that respondent from the data set.
    That's true too, but I was refer to another distinct practice that is often done.

    For example, for the factor of Agreeableness, you might have the sub-traits of: Forgivingness, Gentleness, Flexibility, Patience.

    If an individual is agreeing to most statements, you might normalise the data to allow a meaningful comparison with other individuals.

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    Quote Originally Posted by Subteigh View Post
    That's true too, but I was refer to another distinct practice that is often done.

    For example, for the factor of Agreeableness, you might have the sub-traits of: Forgivingness, Gentleness, Flexibility, Patience.

    If an individual is agreeing to most statements, you might normalise the data to allow a meaningful comparison with other individuals.
    What you are referring to is scale creation, not normalizing of the data. You retain the separate questions pertaining to each sub-trait, but instead of analysing them separately, you analyse them as one over-arching trait called agreeableness. But you only do so if you have evidence from the literature that these sub-traits are correlated and if a Principal Component Analysis (PCA) or Confirmatory Factor Analysis (CFA) shows these sub-traits to be related in your particular data set too.
    Last edited by Armitage; 03-19-2022 at 11:52 AM.

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    Quote Originally Posted by Armitage View Post
    What you are referring to is component analysing, not normalizing of the data. You retain the separate questions pertaining to each sub-trait, but instead of analysing them separately, you analyse them as one over-arching trait called agreeableness. But you only do so if you have evidence from the literature that these sub-traits are correlated and if a Principal Component Analysis (PCA) or Confirmatory Factor Analysis (CFA) shows these sub-traits to be related in your particular data set too.
    I've no idea if that's correct, I'll have to see next time I encounter it. I do remember that it involved lowering the mean scores of certain traits but I don't know how it was done without destroying the quality of the data.

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    Quote Originally Posted by Armitage View Post
    Actually, that's not a reason for normalizing/standardizing the data, instead we use inverted questions to pick up on acquiescence and nay saying. So first we ask if someone agrees or disagrees with the statement "I like peanut butter." only to later in the questionnaire ask them if they agree or disagree with "Peanut butter is disgusting." If they agree with both statements, it's a case of acquiescence, if they disagree with both, then the respondent is a nay sayer. Both acquiescence and nay saying are reasons for filtering out all the answers of that respondent from the data set.




    Yes, but in the scientific community we have agreed based on Lord Fisher, the statistician, of the past century, that any results with a probability of one in five to be caused by chance we deem significant and take seriously, whereas everything weaker with a larger probability of being caused by chance we deem nonsignificant and don't take seriously. @Subteigh, the correlations that you presented are nonsignificant, so scientists agree to not take those data seriously. That doesn't mean that they have been disproved, however, because nothing can ever be disproved in scientific terms and below I explain why so.




    Like Rune tried to explain to you, you can only prove the existence of something, never the non-existence. It sounds counter-intuitive from a layman's perspective, but take for instance the teapot theory. Let's look at Mars through a telescope, we see no teapot flying around Mars. Does this disprove a teapot flying around Mars? According to the layman it does, but the scientist says: "No, not so quickly, we know that for this moment and at this location there might not be a teapot flying around Mars, but have we yet inspected the backside of Mars?" There is always an exception that can be found to enable the possibility of a flying teapot. Of course, this sounds silly, but it is not when instead of teapots we start talking about planets. In 2015 astronomists discovered an interesting gravitationall pull onto Sol, id est the sun, not as in @Sol. They also found erratic orbits of the asteroids in the Kuiper Belt. They hypothesized that this may be explained by a yet undiscovered planet circling around Sol but very far away. https://solarsystem.nasa.gov/planets...et-x/in-depth/

    Previous telescope inspections had not showed the existence of a ninth planet, so a layman would have concluded to be none there. However, scientists never accept something being disproved, they do not accept the null hypothesis, the absence of something, they only retain it as correct for now, but continue searching for exceptions. Another example was the hunt for the Higgs Boson. It had been mathematically theorized decades ago already, but all our particle accelerator experiments showed up nothing. The layman would have concluded the Higgs Boson to not exist, but the molecular scientists continued their search and eventually found it in 2012 with the use of CERN's Large Hadron Collider (LHC), because it achieved top speeds that no other particle collider could. https://www.newscientist.com/article...-to-misbehave/

    A similar issue surrounded nuclear fusion. Even though Sol and every other star is a gigantic fusion reactor, critics said that small, human-made fusion reactors would never be able to generate more energy than was put into them, due to their lack of scale. Previous attempts failed and laymen once again would have concluded the possibility of small scale fusion reactors thereby disproved, but the scientists did not and persevered! Last year we finally generated more energy out of a fusion reaction that we invested into it! https://www.sciencealert.com/for-the...ed-by-the-fuel

    All these examples show why scientists agree that something can never be disproved, even not the possibility of a teapot flying around Mars, because there always might be just that one exception or fact that we don't know of yet.




    Indeed, personality operates more according to continuous scales, than discrete categories. But let's say we take the Big Five personality test with scales from 1 to 10. If someone has 9-10 on openness to new experiences, 5-6 on conscientiousness, 9-10 on extroversion, 3-4 on agreeableness, and 1-2 on neuroticism we call them "Adventurers". When someone attains 1-2 on O, 9-10 on C, 3-4 on E, 3-4 on A, and 3-4 on N we name them "Bureaucrats" instead. We can continue doing this, until we have exhausted all possible combinations, but in the case of 5 10-point Likert scales this would result in 3.125 results and that's when splitting the scales in ranges of 2, like 3-4 for instance. This means that either the labels won't be exhaustive, because you don't have all possible combinations, or you make even larger ranges, either way you lose information. There is thus far more information to be found when using the complete continuous scales, than the discrete categories, yet both the scale and the categorical system are equally valid, they are equally true. The scale system is just more accurate, because it contains more information.

    Socionics being a categorical system doesn't make it untrue per se, it only makes it less accurate. The truth or untruth of the system, id est its validity, instead depends on replicable experiments being done with large samples. If anyone knows if such experiments have been conducted, then it would be @Adam Strange.




    Ice cream consumption and swiming pool visits are correlated, we both agree on that. If I am not at the swimming pool it doesn't mean that I cannot eat an ice cream, though. Nor does it mean that whenever I do eat an ice cream, I have to be at a swimming pool. The golden rule in statistics that correlation does not necessarily imply causation, but causation always implies correlation. In other words, a table is a piece of furniture ( causation always implies correlation ), but not every piece of furniture is necessarily a table (correlation does not necessarily imply causation), even if in some cases the furniture is indeed a table (correlation can at times stem from causation, but it is no guarantee).

    Low levels of conscientiousness and poor health are probably related, I might even have read an article or two about it, but it doesn't mean that if LIEs have high levels of conscientiousness they all will show to be healthy. A LIE who exercises frequently and eats healthily may still develop cancer, because its encoded in their genes without any lifestyle being able to prevent it from developing.

    Not to mention that Socionics Si relates more to being aware of one's body. I'm a LIE, I score relatively high on conscientiousness on the Big Five personality test, and am healthy (despite wanting to shed a few lockdown pounds through exercise soon). I always buy my clothes in physical stores, because I don't have the bodily awareness to get for instance the right size of shoes without the help of a knowledgeable shopkeeper. The last time I bought shoes I had been trying out a pair that I liked and was convinced that they fitted my feet well, only for the shopkeeper to point out to me that they were three sizes too large. Only when he specifically mentioned it did I realize it. Had I bought these shoes online, I would have walked for years in too large shoes without realizing it. I also tend to ignore Si matters, when I was younger I continued walking in my favourite red sneakers, even though by then they had become too small for my feet. At one point even I could no longer ignore the increasing pain I experienced from the pressure, but I think that I continued wearing them for way longer than any higher Si type would have worn them.
    A negative correlation would prove the existence of something - only contrary to what you expect. OK, in this instance, the correlation is weak and in any case doesn't disprove Socionics because Socionics and the Big Five hardly represent the same thing.

    If personality fits on to a standard deviation, with most people not deviating much from the median, that would mean for example that the distinct between ESI and ILE for most people would not be so great, and would be clumped mostly within a standard deviation of the median. Types if they exist may be like personality disorders - most people will not readily fit into one.

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    @Armitage, I wish I'd gone through two semesters of graduate statistics with an LIE like you as an instructor, rather than the ILE I had instead. #wantingpeopletobeyourdual
    Same for the qualitative methods course I took, again had an ILE. Learned very little of practical use. It was more of a philosophy discussion every week
    And had a qualitative & mixed methods course with a timid and very by-the-book, distant N introvert. Gave me some exposure but too much of a summary and review to learn anything in-depth.
    Thank goodness for simplifications and clear explanations out there in other places. Even reading the works of ILE academics (at least ones I type that way...) is easier for me than engaging in open-ended talks with them, since when they write a methods text, they have to commit to some positions in some way (or at least that's my working impression). Their Te demo is very useful for me to understand them.

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    @Shazaam @wonderwoman @Armitage @Foxy Grandpa
    You're correctly typed.

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    @Armitage Russell thought Wittgenstein very amusing/odd for not being able to say "There is no rhinoceros in this room".

    I think in terms of empirical claims, nothing can be said to be certain. But it is possible to say with some level of confidence whether a statement is true or false.

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    @Rune I was just thinking earlier how no one has ever questioned my type, (besides sol when i had first joined here). ha.

    it reminds me of how when i ask for a student discount (#negotiating_tips_from_LIE) and say, "and i have my [student] ID on me", and the clerks don't express any desire to see the ID. that could be their standard practice but in any case i think to myself, "yeah, we can both see how i'm dressed. neither one of us is too 'surprised' to hear me declare myself a student", lol.


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    Quote Originally Posted by Foxy Grandpa View Post
    Means a lot coming from you!
    oh that's cool. Rune and i haven't really interacted / i haven't observed him really to get a read on his weight i would assign to his opinions hehe, kind of a 'frequent emotional neutrality of ILI' vibe, if i had to name one i guess! yep, anyhoo...

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    Quote Originally Posted by wonderwoman View Post
    @Rune I was just thinking earlier how no one has ever questioned my type, (besides sol when i had first joined here). ha.

    it reminds me of how when i ask for a student discount (#negotiating_tips_from_LIE) and say, "and i have my [student] ID on me", and the clerks don't express any desire to see the ID. that could be their standard practice but in any case i think to myself, "yeah, we can both see how i'm dressed. neither one of us is too 'surprised' to hear me declare myself a student", lol.

    It's mainly that you offer to show your student ID out of own volition that convinces them. Someone who isn't a student wouldn't offer to do this out of their own accord, and instead wait and see in the hopes that the store cleric will forget to ask for it. The irony of it is that then specifically the store cleric knows that they have to ask for it.

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    Quote Originally Posted by Subteigh View Post
    That's a common conundrum in psychology. Many studies do include both self-assessment and third party observation. The Big Five does have one of the highest levels of correspondence between those two assessments.

    Many studies normalise the data to adjust for individuals inclined to agree with every statement.
    LOL

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    Quote Originally Posted by Stray Cat View Post
    LOL
    What's the matter?

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    Quote Originally Posted by Stray Cat View Post
    Furthermore, there is always nuance to the human psych that the self isn't aware of and couldn't possibly admit to on one of your "standardized" tests.
    In the case of questioning character flaws, yes, because it is hard to admit those, especially to ourselves. I do think, though, that if Socionics information elements exist, it is possible to create standardized tests for them other than self-report questionnaires. We did a similar thing regarding mental rotation. Psychologists wondered how people conclude that two figures are the same, but rotated, or mirrors that do not fit onto each other. They hypothesized that people would mentally rotate the images in their head to see if they overlap, just like we would do with real figures. The null hypothesis, on the other hand, stated that people would immediately grok the differences. If the null hypothesis was true, this meant that people would not take longer for solving some figures compared to others. If the alternative hypothesis was true, however, people would take longer to solve a figure the more it was rotated away from the other, because they had to rotate it back in their mind, until the two overlapped. This latter explanation turned out true. It is one of my most favourite applied cognitive psychology experiments, because it makes invisible cognitive processes visible even before the advent of advanced brain scanners, such as fMRI.



    Quote Originally Posted by Subteigh View Post
    I've no idea if that's correct, I'll have to see next time I encounter it. I do remember that it involved lowering the mean scores of certain traits but I don't know how it was done without destroying the quality of the data.
    That instead sounds like centering, which is substracting the mean of all the respondents for that variable of each individual score. For instance, let's say you use a questionnaire item called "Love of dogs" of which respondents can report their disagreement or agreement on a scale ranging from 1 to 7. Assume that most respondents feel slightly positive towards dogs, if only just for all the cute puppies there are, so on average people score around 4,2 on our "Love of dogs" item. We then substract this from each individual respondent's answer. So a respondent who scored 5 would turn into one who scored 0,8, while one who scored 2 now scores -2,2. The closer people score towards the average, the closer their new score is to 0. A respondent with a score of 4 would thus become one with a score of -0,2. This way it becomes easily observable if respondents scored below or above the mean. It also helps to normalize the data, which is a fancy term for some criteria data have to fulfill, in order to be properly analysable.

    Most data sampled from large respondent groups is normally distributed by default, but sometimes you have to help the data a bit. Through centralization we can achieve this. The relative differences between the scores are retained, as the difference between respondent A and B is the same regardless of if you use the old values of 5 and 2, or the new ones of 0,8 and -2,2, because the difference remains 3 in either case. However, the original value of the scores is lost. In this case of something abstract like "Love of dogs" on which 1 up to 7 are not concrete values, it doesn't matter, but if we instead measured the number of dogs that one owns, instead of their love of them, this suddenly would become an issue. What does a centralized score of -3.2 dogs mean? It is hardly interpretable.

    When centralizing doesn't show to be sufficient, statisticians go the next step and standardize the data, in order to make it conform to normality. This we do by dividing the new, centralized scores by the standard deviation. The standard deviation is the total difference of each score with the mean. This total difference we then divide by the total number of respondents, so we get the mean total difference of the scores, which we call the variance. If you take the square root of the variance, you obtain the standard deviation. If you standardize data, they basically always come to fall onto the standard distribution and you can analyse them, because the standard distribution is normally distributed. But now the absolute values no longer interpretable, so the -3,2 dogs, but also the relative differences are lost. Respondents A and B no longer differ 3 dogs from each other, but a number of standard deviations from one another. With each transformation even less normally distributed data start behaving normally and thereby become analysable, but at the expense of interpretability.



    Quote Originally Posted by Subteigh View Post
    A negative correlation would prove the existence of something - only contrary to what you expect.
    Yes, if that negative correlation is significant, then we conclude that "Introversion and dog loving are negatively correlated, which instead of showing that introverts like dogs, they actually dislike them." But if the correlation is too weak and thus non-significant we instead say: "We retain the null hypothesis of there being no relationship between introversion and dog loving."
    In either case we cannot jump to the conclusion that introverts are cat lovers, because we did not examine this. Yes, most dog lovers prefer dogs over cats and most cat lovers prefer cats over dogs, but it would be possible that introverts dislike both dogs and cats. We would therefore have to do another study relating introverts with cat loving, then we can say something about introverts being cat lovers, but based on the dog loving study alone we cannot conclude this.


    Quote Originally Posted by Subteigh View Post
    OK, in this instance, the correlation is weak and in any case doesn't disprove Socionics because Socionics and the Big Five hardly represent the same thing.
    Yes and yes, you're getting it.


    Quote Originally Posted by Subteigh View Post
    If personality fits on to a standard deviation, with most people not deviating much from the median, that would mean for example that the distinct between ESI and ILE for most people would not be so great, and would be clumped mostly within a standard deviation of the median. Types if they exist may be like personality disorders - most people will not readily fit into one.
    "If personality fits onto continuous scales" It does actually, that's what the whole Big Five Personality Test is after all, five continuous scales that people can score on.
    ", with people not deviating much from the mean," That's the very definition of the mean, the average score, so most people barely deviate from it, because otherwise it would not be the mean. Or you have some influential outliers. Let's take the average American income, which is an okay $71.456,- ( Statista, 2021, https://www.statista.com/statistics/...yee-in-the-us/ ). But now we exclude all the outliers, so all the Jeff Bezoses, Elon Musks, and Mark Zuckerbergs from the equation. They namely differ substantially from the rest of the population, because the eight richest people own as much as half the poorest of humanity. When you do this, the mean suddenly drops and you find out that the average American actually earns less than $71.456,-. So the $71.456,- is nice for politicians to claim the average American makes. When the rich become richer, the politicians can truthfully claim that the average American income has gone up without the common man earning a single dime more in reality.

    Excluding outliers isn't that desirable either, though, because one study can exclude only the eight richest Americans from the average income, but another could filter out the entire Forbes Billionaires list. The two would thus reach different average American incomes based on these decisions. This is why we take the median when we analyse data prone to many influential outliers, such as income. The median is the middle score. If we have 1.001 respondents and we sort their incomes from small to large, the median income would be the middle one, so the 500th one. Although it is not as easy and informative to calculate with the median, instead of the average, in the case of outlier prone data it is well worth the trade off.

    Then there also exists the mode, which is the number that pops up most frequently. Like the median it is impervious to outliers, yet it can still provide different results than the median. Imagine a "fictional situation" of the United States of America being split in a lower and an upper class. The elite are at the top of the pyramid, whereas the lower class is composed of working men and women. If the data set is hetereogeneous the variance of the lower class is for instance much less, than that of the upper class. This means that most workers earn roughly the same, whereas wealth has more variance, because one can be Ferrari rich, personal yacht rich, or private space rocket rich. If you take the mode, which is the most reoccuring number, then you would take the wage of any of the many common workers. But if you take the median, you might instead end up with a no student debt moderately rich person. In addition, many analyses can work with the median, but not the mode.

    It thus all depends on what data one examines and with what purpose that determines the choice of statistical instruments, but if possible researchers will use the mean and if the data are prone to influential outliers they use the median.


    Quote Originally Posted by Subteigh View Post
    If personality fits on to a standard deviation, with most people not deviating much from the median, that would mean for example that the distinct between ESI and ILE for most people would not be so great, and would be clumped mostly within a standard deviation of the median. Types if they exist may be like personality disorders - most people will not readily fit into one.
    The political compass functions according to similar principles, though with only two axes and fewer categories. https://pbs.twimg.com/media/EZmZDQFX...png&name=large We have a libertarian-authoritarian scale and a state controlled-market controlled scale. There are many data points of which more are centered around the middle than farther away. Still, one can classify different categories. I use the European Parliament as an example, because it actually does have multiple categories. The American system only has two parties in congress, which might mislead one to believe that one could only deduce two categories based on four axes, which is wholly untrue and merely a quirk of the Anglo-Saxon system.

    If we look at the spread of the data the national-conservative European Conservatives and Reformists (ECR), Identity and Democracy, and the non-inscrits share being the most authoritarian of all parties and are pro-market.
    The centre-right European People's Party (EPP) and unaffiliated representatives are less authoritarian, but as right-wing as the national conservative ECR and the non-inscrits.
    The liberal Renew Europe (RE) is distinguishable as the only libertarian pro-market party in the European Parliament.
    The centre-left Socialists and Democrats (S&D) are, as their title implies, centre-left and are thus slightly pro-state. They are also slightly libertarian.
    The Greens-European Free Alliance (Greens/EFA) are as pro-state as the S&D, but even more libertarian.
    The left-wing Gauche Unitaire Européenne/Gauche Verte Nordique (GUE/GVN) is spread in libertarianism amongst the S&D and Greens/EFA, but are more pro-state than either of them.

    Just based on these data points without any colour differences and legend I would be able to recategorize these data points based on their position on these two scales. I might categorize some S&Ds as being unaffiliated, and I would be unable to distinguish all those three authoritarian pro-market parties, but other than that I would be pretty accurate at reclassifying them. I actually created an algorithm that had to classify iris flowers into three different sub-species based on four axes, namely petal and sepal length and width. This clustering algorithm was able to quite accurately categorize the data when comparing its output to the actual sub-species labels of the flowers. It illustrates that it thus is possible to categorize data based on continuous scales, even when the differences are rather small. Here are the flowers: https://s3.amazonaws.com/assets.data...nelearning.png
    And this is what some of the data looks like: http://www.sthda.com/english/sthda-u...and-size-1.png

    The more significant scales you have, the more accurately you will be able to classify groups even when they differ very slightly from one another. But even with two axes it is already possible to relatively reliably create several categories, as illustrated with the political compass. It is thus possible to distinguish most ESIs and EIIs from one another, when provided enough significant scales. But even with few scales it is already feasible to differentiate ESIs and ILEs from one another, which I think the ESIs can confirm, right @Lady Lunacik, @wonderwoman, @Suonani?


    Quote Originally Posted by Subteigh View Post
    Types if they exist may be like personality disorders - most people will not readily fit into one.
    Personality disorders are defined as extreme personality traits, so by definition it would only pertain to a minority of people. But having personality in and of itself is not exclusive to a minority, as all people have personality. Socionics is about personality and is thus applicable to the majority of people, not the minority.
    Last edited by Armitage; 03-20-2022 at 04:34 PM.

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    @Armitage I don't understand the point of reasoning someone who assumes that such and such a type doesn't have X in his functions... Although I understand the initiative, I doubt that there will be a favourable outcome.

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    Quote Originally Posted by Suonani View Post
    @Armitage I don't understand the point of reasoning someone who assumes that such and such a type doesn't have X in his functions... Although I understand the initiative, I doubt that there will be a favourable outcome.
    I don't assume it, rather the complete opposite. It is unproven.

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    Quote Originally Posted by Armitage View Post
    Personality disorders are defined as extreme personality traits, so by definition it would only pertain to a minority of people. But having personality in and of itself is not exclusive to a minority, as all people have personality. Socionics is about personality and is thus applicable to the majority of people, not the minority.
    Personality types in Socionics, if they existed, would also be extreme personality traits.

    Serious psychologists do not take the MBTI seriously, for various reasons, including the fact that the personality of humanity fits onto a standard distribution, with comparatively few extremes.

    Stein, R. and Swan, A.B., 2019. Evaluating the validity of Myers‐Briggs Type Indicator theory: A teaching tool and window into intuitive psychology. Social and Personality Psychology Compass, 13(2), p.e12434. (direct link to pdf file)

    Omori, C.L., 2020. How Average is" Average?" Making Sense of a Machine Learning Analysis of Personality Types. (direct link to pdf file)

    McCrae, R.R. and Costa Jr, P.T., 1989. Reinterpreting the Myers‐Briggs type indicator from the perspective of the five‐factor model of personality. Journal of personality, 57(1), pp.17-40. (direct link to pdf file)

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    Quote Originally Posted by Armitage View Post
    "If personality fits onto continuous scales" It does actually, that's what the whole Big Five Personality Test is after all, five continuous scales that people can score on.
    ", with people not deviating much from the mean," That's the very definition of the mean, the average score, so most people barely deviate from it, because otherwise it would not be the mean. Or you have some influential outliers. Let's take the average American income, which is an okay $71.456,- ( Statista, 2021, https://www.statista.com/statistics/...yee-in-the-us/ ). But now we exclude all the outliers, so all the Jeff Bezoses, Elon Musks, and Mark Zuckerbergs from the equation. They namely differ substantially from the rest of the population, because the eight richest people own as much as half the poorest of humanity. When you do this, the mean suddenly drops and you find out that the average American actually earns less than $71.456,-. So the $71.456,- is nice for politicians to claim the average American makes. When the rich become richer, the politicians can truthfully claim that the average American income has gone up without the common man earning a single dime more in reality.

    Excluding outliers isn't that desirable either, though, because one study can exclude only the eight richest Americans from the average income, but another could filter out the entire Forbes Billionaires list. The two would thus reach different average American incomes based on these decisions. This is why we take the median when we analyse data prone to many influential outliers, such as income. The median is the middle score. If we have 1.001 respondents and we sort their incomes from small to large, the median income would be the middle one, so the 500th one. Although it is not as easy and informative to calculate with the median, instead of the average, in the case of outlier prone data it is well worth the trade off.

    Then there also exists the mode, which is the number that pops up most frequently. Like the median it is impervious to outliers, yet it can still provide different results than the median. Imagine a "fictional situation" of the United States of America being split in a lower and an upper class. The elite are at the top of the pyramid, whereas the lower class is composed of working men and women. If the data set is hetereogeneous the variance of the lower class is for instance much less, than that of the upper class. This means that most workers earn roughly the same, whereas wealth has more variance, because one can be Ferrari rich, personal yacht rich, or private space rocket rich. If you take the mode, which is the most reoccuring number, then you would take the wage of any of the many common workers. But if you take the median, you might instead end up with a no student debt moderately rich person. In addition, many analyses can work with the median, but not the mode.

    It thus all depends on what data one examines and with what purpose that determines the choice of statistical instruments, but if possible researchers will use the mean and if the data are prone to influential outliers they use the median.
    Income does not fit a normal distribution. The Big Five scores for the general population, do.

    Personality is not distributed evenly spaced from low to high, nor is it split into extreme groupings ("personality types").

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    Quote Originally Posted by Armitage View Post
    Yes, if that negative correlation is significant, then we conclude that "Introversion and dog loving are negatively correlated, which instead of showing that introverts like dogs, they actually dislike them." But if the correlation is too weak and thus non-significant we instead say: "We retain the null hypothesis of there being no relationship between introversion and dog loving."
    In either case we cannot jump to the conclusion that introverts are cat lovers, because we did not examine this. Yes, most dog lovers prefer dogs over cats and most cat lovers prefer cats over dogs, but it would be possible that introverts dislike both dogs and cats. We would therefore have to do another study relating introverts with cat loving, then we can say something about introverts being cat lovers, but based on the dog loving study alone we cannot conclude this.
    There's no evidence for what Model A says.

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    Quote Originally Posted by Armitage View Post
    That instead sounds like centering, which is substracting the mean of all the respondents for that variable of each individual score. For instance, let's say you use a questionnaire item called "Love of dogs" of which respondents can report their disagreement or agreement on a scale ranging from 1 to 7. Assume that most respondents feel slightly positive towards dogs, if only just for all the cute puppies there are, so on average people score around 4,2 on our "Love of dogs" item. We then substract this from each individual respondent's answer. So a respondent who scored 5 would turn into one who scored 0,8, while one who scored 2 now scores -2,2. The closer people score towards the average, the closer their new score is to 0. A respondent with a score of 4 would thus become one with a score of -0,2. This way it becomes easily observable if respondents scored below or above the mean. It also helps to normalize the data, which is a fancy term for some criteria data have to fulfill, in order to be properly analysable.

    Most data sampled from large respondent groups is normally distributed by default, but sometimes you have to help the data a bit. Through centralization we can achieve this. The relative differences between the scores are retained, as the difference between respondent A and B is the same regardless of if you use the old values of 5 and 2, or the new ones of 0,8 and -2,2, because the difference remains 3 in either case. However, the original value of the scores is lost. In this case of something abstract like "Love of dogs" on which 1 up to 7 are not concrete values, it doesn't matter, but if we instead measured the number of dogs that one owns, instead of their love of them, this suddenly would become an issue. What does a centralized score of -3.2 dogs mean? It is hardly interpretable.

    When centralizing doesn't show to be sufficient, statisticians go the next step and standardize the data, in order to make it conform to normality. This we do by dividing the new, centralized scores by the standard deviation. The standard deviation is the total difference of each score with the mean. This total difference we then divide by the total number of respondents, so we get the mean total difference of the scores, which we call the variance. If you take the square root of the variance, you obtain the standard deviation. If you standardize data, they basically always come to fall onto the standard distribution and you can analyse them, because the standard distribution is normally distributed. But now the absolute values no longer interpretable, so the -3,2 dogs, but also the relative differences are lost. Respondents A and B no longer differ 3 dogs from each other, but a number of standard deviations from one another. With each transformation even less normally distributed data start behaving normally and thereby become analysable, but at the expense of interpretability.
    Yes, that's the reason it's done. I think that does qualify as normalizing the data.

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    Quote Originally Posted by Armitage View Post
    In the case of questioning character flaws, yes, because it is hard to admit those, especially to ourselves. I do think, though, that if Socionics information elements exist, it is possible to create standardized tests for them other than self-report questionnaires. We did a similar thing regarding mental rotation. Psychologists wondered how people conclude that two figures are the same, but rotated, or mirrors that do not fit onto each other. They hypothesized that people would mentally rotate the images in their head to see if they overlap, just like we would do with real figures. The null hypothesis, on the other hand, stated that people would immediately grok the differences. If the null hypothesis was true, this meant that people would not take longer for solving some figures compared to others. If the alternative hypothesis was true, however, people would take longer to solve a figure the more it was rotated away from the other, because they had to rotate it back in their mind, until the two overlapped. This latter explanation turned out true. It is one of my most favourite applied cognitive psychology experiments, because it makes invisible cognitive processes visible even before the invention of advanced brain scanners, such as fMRI.





    That instead sounds like centering, which is substracting the mean of all the respondents for that variable of each individual score. For instance, let's say you use a questionnaire item called "Love of dogs" of which respondents can report their disagreement or agreement on a scale ranging from 1 to 7. Assume that most respondents feel slightly positive towards dogs, if only just for all the cute puppies there are, so on average people score around 4,2 on our "Love of dogs" item. We then substract this from each individual respondent's answer. So a respondent who scored 5 would turn into one who scored 0,8, while one who scored 2 now scores -2,2. The closer people score towards the average, the closer their new score is to 0. A respondent with a score of 4 would thus become one with a score of -0,2. This way it becomes easily observable if respondents scored below or above the mean. It also helps to normalize the data, which is a fancy term for some criteria data have to fulfill, in order to be properly analysable.

    Most data sampled from large respondent groups is normally distributed by default, but sometimes you have to help the data a bit. Through centralization we can achieve this. The relative differences between the scores are retained, as the difference between respondent A and B is the same regardless of if you use the old values of 5 and 2, or the new ones of 0,8 and -2,2, because the difference remains 3 in either case. However, the original value of the scores is lost. In this case of something abstract like "Love of dogs" on which 1 up to 7 are not concrete values, it doesn't matter, but if we instead measured the number of dogs that one owns, instead of their love of them, this suddenly would become an issue. What does a centralized score of -3.2 dogs mean? It is hardly interpretable.

    When centralizing doesn't show to be sufficient, statisticians go the next step and standardize the data, in order to make it conform to normality. This we do by dividing the new, centralized scores by the standard deviation. The standard deviation is the total difference of each score with the mean. This total difference we then divide by the total number of respondents, so we get the mean total difference of the scores, which we call the variance. If you take the square root of the variance, you obtain the standard deviation. If you standardize data, they basically always come to fall onto the standard distribution and you can analyse them, because the standard distribution is normally distributed. But now the absolute values no longer interpretable, so the -3,2 dogs, but also the relative differences are lost. Respondents A and B no longer differ 3 dogs from each other, but a number of standard deviations from one another. With each transformation even less normally distributed data start behaving normally and thereby become analysable, but at the expense of interpretability.





    Yes, if that negative correlation is significant, then we conclude that "Introversion and dog loving are negatively correlated, which instead of showing that introverts like dogs, they actually dislike them." But if the correlation is too weak and thus non-significant we instead say: "We retain the null hypothesis of there being no relationship between introversion and dog loving."
    In either case we cannot jump to the conclusion that introverts are cat lovers, because we did not examine this. Yes, most dog lovers prefer dogs over cats and most cat lovers prefer cats over dogs, but it would be possible that introverts dislike both dogs and cats. We would therefore have to do another study relating introverts with cat loving, then we can say something about introverts being cat lovers, but based on the dog loving study alone we cannot conclude this.




    Yes and yes, you're getting it.




    "If personality fits onto continuous scales" It does actually, that's what the whole Big Five Personality Test is after all, five continuous scales that people can score on.
    ", with people not deviating much from the mean," That's the very definition of the mean, the average score, so most people barely deviate from it, because otherwise it would not be the mean. Or you have some influential outliers. Let's take the average American income, which is an okay $71.456,- ( Statista, 2021, https://www.statista.com/statistics/...yee-in-the-us/ ). But now we exclude all the outliers, so all the Jeff Bezoses, Elon Musks, and Mark Zuckerbergs from the equation. They namely differ substantially from the rest of the population, because the eight richest people own as much as half the poorest of humanity. When you do this, the mean suddenly drops and you find out that the average American actually earns less than $71.456,-. So the $71.456,- is nice for politicians to claim the average American makes. When the rich become richer, the politicians can truthfully claim that the average American income has gone up without the common man earning a single dime more in reality.

    Excluding outliers isn't that desirable either, though, because one study can exclude only the eight richest Americans from the average income, but another could filter out the entire Forbes Billionaires list. The two would thus reach different average American incomes based on these decisions. This is why we take the median when we analyse data prone to many influential outliers, such as income. The median is the middle score. If we have 1.001 respondents and we sort their incomes from small to large, the median income would be the middle one, so the 500th one. Although it is not as easy and informative to calculate with the median, instead of the average, in the case of outlier prone data it is well worth the trade off.

    Then there also exists the mode, which is the number that pops up most frequently. Like the median it is impervious to outliers, yet it can still provide different results than the median. Imagine a "fictional situation" of the United States of America being split in a lower and an upper class. The elite are at the top of the pyramid, whereas the lower class is composed of working men and women. If the data set is hetereogeneous the variance of the lower class is for instance much less, than that of the upper class. This means that most workers earn roughly the same, whereas wealth has more variance, because one can be Ferrari rich, personal yacht rich, or private space rocket rich. If you take the mode, which is the most reoccuring number, then you would take the wage of any of the many common workers. But if you take the median, you might instead end up with a no student debt moderately rich person. In addition, many analyses can work with the median, but not the mode.

    It thus all depends on what data one examines and with what purpose that determines the choice of statistical instruments, but if possible researchers will use the mean and if the data are prone to influential outliers they use the median.


    The political compass functions according to similar principles, though with only two axes and fewer categories. https://pbs.twimg.com/media/EZmZDQFX...png&name=large We have a libertarian-authoritarian scale and a state controlled-market controlled scale. There are many data points of which more are centered around the middle than farther away. Still, one can classify different categories. I use the European Parliament as an example, because it actually does have multiple categories. The American system only has two parties in congress, which might mislead one to believe that one could only deduce two categories based on four axes, which is wholly untrue and merely a quirk of the Anglo-Saxon system.

    If we look at the spread of the data the national-conservative European Conservatives and Reformists (ECR), Identity and Democracy, and the non-inscrits share being the most authoritarian of all parties and are pro-market.
    The centre-right European People's Party (EPP) and unaffiliated representatives are less authoritarian, but as right-wing as the national conservative ECR and the non-inscrits.
    The liberal Renew Europe (RE) is distinguishable as the only libertarian pro-market party in the European Parliament.
    The centre-left Socialists and Democrats (S&D) are, as their title implies, centre-left and are thus slightly pro-state. They are also slightly libertarian.
    The Greens-European Free Alliance (Greens/EFA) are as pro-state as the S&D, but even more libertarian.
    The left-wing Gauche Unitaire Européenne/Gauche Verte Nordique (GUE/GVN) is spread in libertarianism amongst the S&D and Greens/EFA, but are more pro-state than either of them.

    Just based on these data points without any colour differences and legend I would be able to recategorize these data points based on their position on these two scales. I might categorize some S&Ds as being unaffiliated, and I would be unable to distinguish all those three authoritarian pro-market parties, but other than that I would be pretty accurate at reclassifying them. I actually created an algorithm that had to classify iris flowers into three different sub-species based on four axes, namely petal and sepal length and width. This clustering algorithm was able to quite accurately categorize the data when comparing its output to the actual sub-species labels of the flowers. It illustrates that it thus is possible to categorize data based on continuous scales, even when the differences are rather small. Here are the flowers: https://s3.amazonaws.com/assets.data...nelearning.png
    And this is what some of the data looks like: http://www.sthda.com/english/sthda-u...and-size-1.png

    The more significant scales you have, the more accurately you will be able to classify groups even when they differ very slightly from one another. But even with two axes it is already possible to relatively reliably create several categories, as illustrated with the political compass. It is thus possible to distinguish most ESIs and EIIs from one another, when provided enough significant scales. But even with few scales it is already feasible to differentiate ESIs and ILEs from one another, which I think the ESIs can confirm, right @Lady Lunacik, @wonderwoman, @Suonani?




    Personality disorders are defined as extreme personality traits, so by definition it would only pertain to a minority of people. But having personality in and of itself is not exclusive to a minority, as all people have personality. Socionics is about personality and is thus applicable to the majority of people, not the minority.
    Yeah. If you grab a camera & film lions you'll eventually realize how quick they are to satiate their bodily desires.

    A "standardized" test could be created for socionics but, in my opinion, a person cannot be psychologically cognizant of the meaning of each question.

    Perhaps, you yourself could create a standardized socionics test?

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    Quote Originally Posted by Suonani View Post
    @Armitage I don't understand the point of reasoning someone who assumes that such and such a type doesn't have X in his functions... Although I understand the initiative, I doubt that there will be a favourable outcome.
    The discussion with Subteigh seems to go in a good mood, which is important to me. It's not the kind of discussion in which I try to convince the other as much as that it is a debate for fun. It tickles my NT-ness.



    Quote Originally Posted by Subteigh View Post
    Income does not fit a normal distribution.
    It actually does the moment that you conduct a logarithmic transformation over it, because there are many poor people and few rich ones. The distribution is right skewed, because it has a very long tail on its right. For such extremely skewed data logarithmic transformations are perfect.


    Quote Originally Posted by Subteigh View Post
    The Big Five scores for the general population, do.
    Yes


    Quote Originally Posted by Subteigh View Post
    Personality is not distributed evenly spaced from low to high,
    Yes, it's no uniform distribution, indeed. Most distributions in nature are normal, not uniform.


    Quote Originally Posted by Subteigh View Post
    nor is it split into extreme groupings ("personality types").
    You can cluster multidimensional data into groupings, that's what factor analysis does and that's a tried and true method.


    Quote Originally Posted by Subteigh View Post
    There's no evidence for what Model A says.
    The negative dog loving introverts example was meant more regarding your comment on negative correlations.


    I cannot open this one, because it says that I'm misdirected.


    This study actually discusses how the researchers of another study were rather liberal in the interpretation of their results. Those other researchers developed a new personality typing tool based on machine learning, but the validity of this novel tool they took too loosely, so they could publish the results.


    This study tries to validate MBTI by comparing it to an established personality test, the NEO-PI. They conclude that the Extroversion-Introversion, Sensing-Intuition, Feeling-Thinking, judging-perceiving dichotomies are actually continuous scales, which I concluded a long time ago already. We do not disagree on that, I too believe these items to represent scales and not clearly marked borders between one or the other. I think that everyone agrees on that, including the Socionics questionnaire developers, because they include percentages in the outcomes. That the judging-perceiving scale does not have all that great construct validity does not surprise me, because there's a lot of theoretical confusion about it if we look alone at the differing interpretations of it between Socionics and MBTI.



    Quote Originally Posted by Stray Cat View Post
    Yeah. If you grab a camera & film lions you'll eventually realize how quick they are to satiate their bodily desires.
    LOL


    Quote Originally Posted by Stray Cat View Post
    A "standardized" test could be created for socionics but, in my opinion, a person cannot be psychologically cognizant of the meaning of each question.

    Perhaps, you yourself could create a standardized socionics test?
    I get that, which is why it might be more desirable to use puzzles and story scenarios to test the information elements, like is done in many other psychological tests.
    Fun proposal, I've actually been giving it some thought myself, but as a master student I don't have the authority, unfortunately. I'm allowed to come up for my thesis with a topic that spans at most three months, this sounds more like a PhD project. Hah, it actually might not be that bad an idea. And in a way the development and validation of a new scale would fall under statistics. I'll keep that one in mind. It would be fun to research. But for my master thesis I'm probably going to do local minima optimization, so to lower the noise of data, because my programming professor is doing that. Or developing a Game Theory application for the Prisoner's Dilemma and Rock-Paper-Scissors, because my graduation supervisor is busy with this.
    Last edited by Armitage; 03-19-2022 at 08:14 PM.

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