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PSYC3980: Chapter 8 Notes

by: Brittany Ariana Borzillo

PSYC3980: Chapter 8 Notes PSYC3980

Marketplace > University of Georgia > Psychology > PSYC3980 > PSYC3980 Chapter 8 Notes
Brittany Ariana Borzillo
GPA 3.7

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class notes used as the backbone of the notes but they're filled in and supplemented with book notes
Research Methods in Psychology
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This 3 page Class Notes was uploaded by Brittany Ariana Borzillo on Thursday September 29, 2016. The Class Notes belongs to PSYC3980 at University of Georgia taught by in Fall 2016. Since its upload, it has received 2 views. For similar materials see Research Methods in Psychology in Psychology at University of Georgia.


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Date Created: 09/29/16
C HAPTER 8: B IVARIATE C ORRELATIONAL R ESEARCH A SSOCIATION  Describes relationship between 2 measured variables  Assessment  Bivariate Correlation o Strength  Strong, weak, none o Direction  Positive, negative, none o Scatterplots  Strong  positive  Weak  negative  Assesses with correlation coefficient (r)  0.1 = small/weak  0.3 = medium/moderate  0.5 = large/strong o Categorical variables  Bar graphs more accurately represent correlation  T-test  Tests statistical difference between means V ALIDITIES OF ASSOCIATION C LAIMS  Most important o Construct  Assesses how well are variables defined/measured  Face  the degree to which a procedure, especially a psychological test or assessment, appears effective in terms of its stated aims  Content  the extent to which a measure represents all facets of a given construct  Predictive  extent to which a score on a scale or test predicts scores on some criterion measure  Convergent  refers to the degree to which two measures of constructs that theoretically should be related, are in fact related  discriminant  tests whether concepts or measurements that are not supposed to be related are, in fact, unrelated o Statistical  Effect size  Describes strength of an association  Stronger effect size leads to more accurate predictions  Usually indicates more important results  Statistical significance  Inferential statistics o How likely are results to be due to chance o Use probabilities to understand what the data represents and how to extrapolate from sample to population  Assess the probability of getting the results if the actual association in population is zero o Cannot collect population information, sample must be able to estimate  Probability value = p o Range is between 0 and 1  Cannot be represented as a negative o If p is close to 0, it unlikely that a result comes from the population that has a true correlation of zero o If p is closer to 1, it’s likely that the result comes from population where true correlation is zero  Null hypothesis o the hypothesis that there is no significant difference between specified populations, any observed difference being due to sampling or experimental error  Statistically significant depends on effect size and sample size o Smaller sample sizes are more effected by chance  Outliers  Extreme scores  Can have a large effect on correlations  Both variables can have outliers o Shared or independent from one another  Restriction of Range  Aren’t sampling from the entire range of either variable  Curvilinear Relationships  Simple bivariate correlations (r) only assess linear relationships  Also important but less necessary o Internal  Not formally assessed  People mistakenly try to make casual claims for correlational research  Should not be done because causal claims require covariance between cause and effect, temporal precedence, and must not have any confounding variable  Subgroup problem  Can’t rule out a third variable which leads to spurious associations  Moderation o Relationship between 2 variables changes depending on the level of a third variable o Could strengthen or weaken a relationship unjustly o External  Subgroup problem  Can’t rule out a third variable which leads to spurious associations  Moderation o Relationship between 2 variables changes depending on the level of a third variable o Could strengthen or weaken a relationship unjustly


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