Research methods in psychology: Design and data analysis Study Guide Chapter 1 of Gleitman et al., pp. 12-33 And conferences of Th/Fri Aug 30/31. See also Reading Guide for Strack et al. The terms in bold are particularly important. They will be used frequently, by all instructors, throughout the year. The empirical approach formulating testable hypotheses anecdotal evidence reporting bias observation confirmation bias previous literature (theories and data) file-drawer problem (a type of reporting bias) defining the independent and dependent variables collecting the data (see below) evaluating the data (see below) drawing conclusions confirming the hypothesis (NOT proving, see p. 14) disconfirming the hypothesis suggesting further avenues of study replications elaborations formulating new hypotheses collecting the data: types of research designs experiments between-group designs random assignment to groups “matched” assignment to groups (example in second paragraph of p. A1) within-subject designs case studies observational studies correlational studies direction of causality third variable problem collecting the data: internal validity associated with the independent variable(s) proper selection of the "control" condition minimizing demand characteristics double-blind design eliminating confounds counterbalancing (example in last paragraph of p. 21) associated with the dependent variable(s) does the dependent variable measure what you want it to? scales: categorical, ordinal, interval, ratio (see pp. A2-A4) Psy 121 Fall, 2007 Study Guide 2 defining the independent and dependent variables: external validity selecting the sample ecological validity ethics in psychology research informed consent debriefing evaluating the data: GRG Appendix And conferences of Thurs/Fri Sept 6/7 frequency distributions, histograms normal distributions skewed distributions measures of central tendency: mean, median, mode measures of variability range variance standard deviation statistical tests correlation coefficient (r) positive and negative correlations correlation does not imply causation hypothesis testing null hypothesis “critical ratios”: t-test: comparison of two means (one indep variable with two levels) two independent means (between-groups design) paired means (within-subjects design) Analysis of variance (ANOVA, F-test) comparisons involving more than two means one independent variable with more than two levels more than one independent variable main effects interactions p-value (probability)