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Unformatted text preview: 3/18/2008 1 Psyc110 March 18, 2008 Carryover material Psyc109 material Scatterplots Covariance (cov XY ) ◦ Computation Pearson’s r ◦ Computation ◦ Hypothesis testing Calculating variances and standard deviations Logic of hypothesis testing ◦ Comparing calculated sample statistics to hypothesized population parameters ◦ Greek characters for hypothesis notation Sampling distributions (generally) Correlations = two-tailed tests (default) 3/18/2008 2 p values ◦ So far: p as alpha level = probability of Type I error… ◦ But this actually means: “the probability of a sample effect this large if the true population effect is zero” ◦ “Effect” could be: Mean difference Correlation ◦ Every t , z , statistic we calculate has an exact p value Given by SPSS in the “Sig.” box p < .05 and p < .01 are arbitrary cutoff points Correlational research approach… ◦ See how pre-existing variability in one, predictor , variable is related to variability in another, criterion , variable ◦ Correlational statistics express the relationship between two or more variables Pearson correlation – r – two variables only Regression – two or more variables “Correlation does not equal/imply causation!” Pearson’s r ◦ Quantifies relationship between two variables Gives us two valuable pieces of information: (1) The strength...
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This note was uploaded on 05/05/2008 for the course PSYCH 110 taught by Professor Burt during the Spring '08 term at Vermont.
- Spring '08