2.  Descriptive Methods ◦ Observation ◦ Survey Research  Experimental Methods ◦ Independent Groups Designs ◦ Repeated Measures Designs ◦ Complex Designs  Applied Research ◦ Single-Case Designs and Small-n Research ◦ Quasi-Experimental Designs and Program Evaluation

3.  PSYCHOLOGICAL EXPERIMENTS  LOGIC OF EXPERIMENTAL RESEARCH  RANDOM GROUPS DESIGN ◦ Block Randomization ◦ Threats to Internal Validity  ANALYSIS AND INTERPRETATION OF EXPERIMENTAL FINDINGS ◦ The Role of Data Analysis in Experiments ◦ Describing the Results ◦ Confirming What the Results Reveal ◦ What Data Analysis Can’t Tell Us  ESTABLISHING THE EXTERNAL VALIDITY OF EXPERIMENTAL FINDINGS  MATCHED GROUPS DESIGN  NATURAL GROUPS DESIGN Independent Groups Designs

4.  Experiments: ◦ Empirical testing of hypotheses ◦ Testing contemporary theories ◦ Identification of the causes of behavior ◦ Testing intervention

5.  Manipulation ◦ IV on DV to observe the effect on behavior  Experimental control ◦ causal inference (IV caused the observed changes in the DV) ◦ Control is an essential ingredient ◦ gained through manipulation, holding conditions constant, and balancing  Causal Inferences (three conditions) ◦ covariation, time-order relationship, and elimination of plausible alternative causes.  When confounding occurs, a plausible alternative explanation for the observed covariation exists, and therefore, the experiment lacks internal validity. Plausible alternative explanations are ruled out by holding conditions constant and balancing

6.  Each group of subjects participates in only one condition of IV  Comparable groups ◦ Manipulation: Random assignment of conditions ◦ Holding Conditions Constant ◦ Balancing or averaging subject characteristics (individual differences) ◦ independent groups for the levels of the independent variable  Dittmar et al. (2006) ◦ Barbie,Emme, neutral

8.  Intact groups: ◦ Potential confounding due to preexisting differences  Balancing Extraneous Variables ◦ Experimenter, observer  Selective subject loss > Mechanical subject loss  Demand characteristics  Placebo control groups  Double-blind experiments

9.  Good research question  Good experiment  Role of Data Analysis in Experiments  Statistics as Principled Argument (1995) by Robert Abelson ◦ “primary goal of data analysis is to determine whether observations support a claim about behavior”  Replication  Reliability  Data analysis and statistics  Alternative to replication

10.  Descriptive statistics that ◦ Mean (central tendency) ◦ Standard deviation (variation/individual differences)  Measures of effect size ◦ strength of the relationship and they are not affected by sample size. ◦ Cohen’s’ d: More than mean difference ◦ difference between two group means r elative to the average variability ◦ small, medium, and large effects (.20,.50, and.80)  Meta-analysis ◦ Measures of effect size to summarize the results of many experiments investigating the same independent variable or dependent variable

11.  Inferential statistics ◦ Reliable effect of IV on DV? ◦ To infer results of sample on population ◦ Difference due to chance (error variance)  Two methods (Null hypothesis testing and confidence intervals)  NHST ◦ Probability theory whether difference is due to error variance ◦ T-test, F-test etc. ◦ A statistically significant = small likelihood of occurring if the null hypothesis < 5%  confidence intervals ◦ Probability of CI (.95) ◦ Width of interval (the narrower the better) ◦ Degree of overlap  reliable difference of sample means

12.  Results of study have practical value or even if they are meaningful?  No certainty regarding conclusion  Errors: ◦ A Type I error: is like a false alarm—saying that there is a fire when there is not ◦ Type II error: we have insufficient evidence to reject the null hypothesis and it is, in fact, false

13.  External validity ◦ Application to other individuals, settings, and conditions  Theory-testing  Emphasis on internal validity over external validity  Field experiments  increase the external validity  Partial replication  external validity  Generalization of conceptual relationships

14.  A matched groups design ◦ Too few subjects available for random assignment to work effectively  Matching ◦ Best on the dependent variable tasks  After matching task ◦ Random assignment to the conditions

15.  Individual differences variables (or subject variables) are selected rather than manipulated to form natural groups designs.  The natural groups design represents a type of correlational research in which researchers look for covariations between natural groups variables and dependent variables.  Causal inferences cannot be made regarding the effects of natural groups variables because plausible alternative explanations for group differences exist.