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Lecture 5

# Lecture 5.doc

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School
Department
Psychology
Course
PSYC 2600
Professor
Chris Motz
Semester
Winter

Description
Lecture 5 Tuesday, January 18, 2011 - We’re about to get started on the first domain of knowledge - We’ll finish up Ch. 2 stuff, then we’ll get started on Ch. 3 (dispositional domain) o Focus of dispositional domain: traits o Rest of the course will feed off of this domain (connecting all other research back to traits) o The modern approach - 3 fundamental questions that guide psychologists who study traits—main point in Ch. 3 - Last week’s notes - Inferential statistics o Collect data from study sample, find a trend/pattern o You’re rarely interested in just the sample o You want to generalize to larger population—is the data significant? o FIRST FUNDAMENTAL QUESTION: are the results due to chance? Are they significant?  Could find that it is significant (meaningful difference between groups), or could find the results were out of chance (didn’t account for some other variable, etc.) o Need a certain sample size to get over individual differences—could have 20 people in the study o But it could be that you chose a biased sample  **More prone to getting wrong results with a small group—the biased sample gets offset amongst a huge sample size o Larger groups—more confidence in the accuracy o But up to a certain point. There are statistical ways of figuring out what sample size you need. It varies.  MRI experiments are extremely expensive, takes a long time to schedule appointments, would want a smaller sample size.  But difference would be strong enough to make up for the small sample size o Big control factor for getting over the chance probability: repeating the study, changing the manipulation a little to get at it with a different angle (tiny probability of getting results by chance five times in a row) o *Statistical significance: from outcome of analyses, claim that pattern in data is not due to chance o Making sense of measures (questionnaires, scales)—ask whether it’s reliable, valid, and generalizable o *Reliability: extent to which test measures the real level of that trait  *Test-retest: re-administer questionnaire to same group of people (hour, week, etc. later)—should score about the same both times • This only works if it’s a fairly consistent variable (ex. Level of neuroticism, extroversion, self-esteem—they’ll get some minor wobbles, but fairly consistent) • Otherwise, either measure is not reliable or you’re not thinking right about the trait  *Inter-rater reliability: consistency among the different judges so there’s correlation  *Internal consistency reliability: do all the individuals questions correlate with the scores on the rest of the group? (the scores on the one question should correlate with the scores on the others) • Otherwise, the question isn’t doing what you want it to do o *Validity: degree to which test measures what it claims to measure  Ex. Measuring height—might give reliable results but is not an indicator of self-esteem.  *Questionnaire can be reliable without being valid. But if it’s not reliable, it can’t be valid.  Types of validity: • Face validity: does it look like it’s measuring what it’s supposed to? (But we don’t necessarily always want to maximize this particular form of validity) • Predictive/criterion validity: does it predict some external criteria/behaviour? (Ex. Do scores on happiness questionnaire correlate with happy behaviours?) • Convergent validity: do the scores of this measure correlate with other, older measures we used to use? • Discriminant validity: do the scores not correlate with other measures it’s not supposed to correlate with? (discriminate between self-esteem and extroversion) • Content validity: does the test encompass the full range of the concept? (openness to experience is just limited to foods, it’s sampling from a very narrow range of content) • Construct validity: THE BIG ONE- takes into account all the other types- essentially the same as the general definition for validity- does the test measure what it claims to measure? o *Generalizability: extent to which questionnaire is valid across different areas of behaviour (different conditions/people)  Maybe our measure only relates to females, males, in a certain context (locus of control—can assess it in school, at work, when it comes to family—but on our online questionnaires, we have very specific scale that’s not generalizable—specifically related to health-related behaviours)  Sometimes we want very specific measure—to see whether seeking help would lead to solution, following through with medication, etc.  But most of the time, we want to generalize  Takes into account both reliability and validity - One study takes all these concepts and puts them together o By Buss (lead researcher in personality psychology, also the author of textbook) o Personality and mate preferences- five factors in mate selection and marital satisfaction o Big Five: extroversion, agreeableness, conscientiousness, neuroticism, openness to experience o Assortative mating—idea that like attracts like—we look for people who are similar to ourselves (as opposed to opposites attract)  This is the general trend for people  Evidence indicates that this is true for a number of different demographic variables: socioeconomic status, type of career, religious background, height, etc. o But at the time, there was very little evidence that personality was also working this way o Goals of study:  Figure out which personality characteristics are viewed as desirable  Do the sexes differ in how exacting they’re going to be on certain personality dimensions?  Evaluate the degree of assortative mating across a wide variety of personality variables  Whether we actively pursue those who are similar to ourselves  To assess whether expressed preference connects to who people actually get  To evaluate whether a failure to get the preferences leads to unhappiness o Did this with dating and married couples o Ch. 3 is all about the big five traits- nice segway o *We’re primarily interested in marital satisfaction o Self-report data: each participant rated himself/herself on the big five (self-report questionnaire) o Observer-report data: from significant other, from professional observer  *triangulation- gathering data from variety of sources o Self-report data: each participant rated himself/herself on mate preferences o Results: **  Women were a little more exacting- desired higher levels of variety of socially desirable characteristics in mates  Individual differences for desired characteristics- generally prefer mates who are similar to ourselves • Actually obtain mates who are close to what we desire  Personality characteristics of significant other predicts marital and sexual satisfaction  This is quite specific most notably when our partner is lower than what we want on agreeableness, emotional stability (opposite of neuroticism), openness  Both agreeableness and openness to experience: most valued personality traits for both sexes
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