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# Individual Differences Study Guide Benchmark 1 PSY 345

UT

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This 9 page Study Guide was uploaded by Cimmi Alvarez on Thursday September 8, 2016. The Study Guide belongs to PSY 345 at University of Texas at Austin taught by Elliot Tucker-Drob in Fall 2016. Since its upload, it has received 89 views. For similar materials see Individual Differences in Psychology (PSYC) at University of Texas at Austin.

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Date Created: 09/08/16

Study Guide Psychometrics Act of measuring psychological features-distributed in bell(normal) curve Ways to Organize Personality Taxonomy Big 5 Hierarchal Personality Hexagonal Structure Ways to Organize abilities Cognitive Map Chart Evolution and Variations Person without ideal sociability/intellect will not be able to reproduce Evolution is selecting but there is still diversity Experimental Psychology Scientific psychology is about understanding knowledge for knowledge’s sake, not developing treatments Just understanding it Average differences between groups of people attributable to situations, manipulations, and intervention. Groups experimenter designed randomly Treated the same- the groups will be the same Treats groups differently- observes what happens Have control and experimental groups Aspects Experimenter controlled Random assignment Interference cost- difference between average of two groups Individual Differences psychology Person-to-person differences inherent to individuals Naturally occurring How people differ from one another Chronbocks sweet spot- take what we know about people and understand the difference based on what we did Aptitude by treatment interactions- how much you have the capacity to learn from an intervention and how much treatment helped Person by situation interactions Measurement The quantification of the attributes of objects Quantifying- makes psychology scientific, turning observations into quantitative data. Not just a person but a characteristic ex: Extraversion Qualitative- sitting in a room talking to people and making decisions Physical attributes are directly observable, psychological attributes are theoretical constructs Theoretical constructs 2 must be inferred from what are presumed to be their behavioral manifestations Constructs- we construct them and are not able to directly observe Can’t measure these traits themselves, observe behaviors presumed to reflect it to measure instead Operational Definition The process of creating rules that relate unobservable constructs to observable behaviors To compare individuals in how much variation of a construct they possess have to quantify observable behaviors Levels of Measurement Nominal If numbers are used, they are labels, do not have any meaningful order Ordinal People ordered on the amount of the construct, but the difference between scores is not meaningful. Interval The difference between the scores is meaningful Can’t compare the ratios because there is no meaningful 0 point Psychological tests are assumed to be measured on this scale Ratio Most meaningful. Meaningful 0 point. Allows nonzero values to be expressed as ratios of one another. Standard Scores and the Normal Distribution 3 Distribution is characterized by what scores look like when they are distributed on a graph Normal distribution-symmetrical bell shaped graph Number of people with scores that differ from the average decreases as scores get more extreme (both high and low) Normal Distribution characterized by Mean Average of the scores- add all scores and divide by the number of scores Variances Spread of the scores (how wide is the distribution)- averaged squared difference between each score and the mean then divide by the number of scores Standard Deviation Square root of the variance Standard Scores (z-scores) Take the score subtract the mean and then divide by standard deviations. Make scores directly Comparable-Is the number of standard deviations from the mean the score is. 1.96 Standard deviations: + 97.5%; - 2.5% Distribution in standard scores have a mean of 0 and SD of 1 Correlation and Regression quantifies how two different variables are related to each other Indexing tendency but not predicting it perfectly Correlation 0-flat slope, no correlation; + positive scores indicate positive scores; - scores indicate negative scores. 1 or -1 perfect. 4 Closer to 0 less correlation R squared- what percentage is explained by the correlation Correlations does imply causation but just don’t know where it is coming from but does show something is causing the two variables to be related. One variable causes another A third variable causes both Both variables represent same underlying construct Two variables represent two different constructs that are related Error causes the variables- no correlation happening by chance P values Confirm correlation is unlikely caused by chance (low p value) around P=.05 then causation holds. Magnitude of correlation Index of how strongly two variables are related to each other Correlation is linear regression with z scores Regression is linear regression with raw scores Classical Test Theory Formula Score=True score + Error Y=T+E Error- white noise in our measurement Come from Measurements made with imprecision (especially in psychology) Can’t perfectly test anything Reliability of tests- how ell that test represents the true score 5 Reliability Used to estimate proportion of variation in the test scores can be attributed to the construct that the test was designed to measure (as opposed to error) Internal Consistency How much the items within the test correlate with one another Cronbach’s alpha- average correlation between each item in the test Split Half Reliability- correlation between two halves of the test Test-Retest Reliability- correlation between scores on two administrations of the test If high correlation then good reliability Take the correlation and subtract from one equals t he percentage of error Traits Characteristics of an individual that are relatively stable and enduring Individual changes happen to traits over longer periods of time Use Test-Retest States Momentary moods, feelings, or capabilities that are prone to fluctuation, and are often sensitive to physiological situational influences. Intraindividual variability happens Use internal consistency Validity 6 Extent to which a measurement assess the characteristic that it is supposed to Face – Does the test appear to measure what it is supposed to? Criterion-Oriented Validity -Whether or not the test scores predict some criterion of interest Concurrent Validity Test score and the criterion are determined at essentially the same time Predictive Validity The test score issued to predict a later outcome Content Validity Are the items a representative sample of the universe of items that the researcher is interested in Construct Validity Process of better understanding exactly what the construct is that is being measured Occurs whenever no criterion or universe of content is accepted entirely adequate to define the characteristic of interest. Logic Begin understanding construct by documenting network of relations that items have with other variables Summarize relations with general laws induced from them Interlocking systems of laws help define construct termed “the nomological network”- network of laws Construct studied extensively and network develops begins to involve relations among multiple unobservable constructs 7 Bring it down to something measurable scientifically. Some laws must have implications for relations among unobservable attributes Don’t make predictions about what is already considered true Convergent Validity Different tests converge on the same construct (high Correlations) Discriminant Validity Test that are supposed to measure different constructs should not correlate (Low Correlations) Psychometrics Subfield of psychology that is focused on the measurement of psychological traits Self report tests Answers questions about his or her actions, thoughts, and feelings in various situations Informant Reports Information about targets typical behaviors and interactions is provided by informant who know the examinee well Direct Observation Record instances, duration, or frequency of particular behaviors Biodata (life record data) Records of a persons life that are relevant to the trait in question Objective Testing Test that have objectively correct answers, and tests in which there are clear forms of ideal performance 8 Conspective Tests Conspective (structured) I can be unambiguously scored even if there is no correct answer Strategies of Test Construction Empirical Strategy Large pool of items are gathered then administered to a group who are also measured on some other criterion. Items that highly correlate with criterion others are thrown out. Picking best predictors of outcome regardless of why they might be related Factor Analytic (and other Multivariate) Strategies Large pool of test items gathered and administered to participants. Items that correlate with one other are grouped together and items that do not correlate are in different groups. Each group represents a trait Rational Strategy Pure logic to come up with a test that measures what you are interested in 9

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