LEARNING OBJECTIVESLEARNING OBJECTIVESLEARNING OBJECTIVESLEARNING OBJECTIVESStudy Guide for Final Exam Psychology 300Dr. StangorCHAPTER 11:EXPERIMENTAL RESEARCH: FACTORIAL DESIGNSLEARNING OBJECTIVES1. Understand what factorial designs are and what advantages they have over other experiments.- Experimental designs with more than one independent (manipulated) variable- The use of more than one independent variable in a single experiment increases the amount of info that can be gained- Also always cheaper in terms of number of research participants2. Determine what is meant by crossing the factors in a factorial design.- In factorial designs, the conditions are arranged such that each level of each independent variable occurs with each level of the other independent variables- Known as “crossing” the factors3. Understand main effects, interactions, and simple effects.- Main effect- differences on the dependent measure across the levels of any one factor, controlling for all other factors in the experiment - Interactions- pattern of means that may occur in a factorial experimental design when the influence of one IV on the DV is different at different levels of another IV or variables- Simple effects- effect of one factor within a level of another factor4. Show some of the possible patterns that interactions can take.-5. Determine how data from a factorial design is presented in the research report.-6. Define a mixed factorial design.- Design in which some factors are between participants and some are repeated measures7. Understand the purpose of means comparison and what statistical techniques are used to compare means.- Used both in one-way designs with more than 2 levels and in factorial designs- For more specific information about the significance of the simple effects- Conducted to discover which group means are significantly different from each otherSAMPLE QUESTIONS 1. Discuss when factorial experimental designs might be used, and their advantages over one-way experiments.- More than one independent variable2. Define main effects, simple effects, and interactions. 3. What data from a factorial research design need to be reported in the research report, and how are they so reported?- F values for each of the main effects and interactions- Within groups sum of squaresChapter 14: Quasi-Experimental Research Designs 103- Degrees of freedom- Mean squares (labeled residual rather than within groups)- Similar to that of a one way design except that more means and F tests need to be reported4. What are mean comparisons? Differentiate pairwise and complex comparisons, as well asplanned and post hoc comparisons. Explain how each type of comparison is used in research.- Pairwise comparisons- most common, means comparison in which any one condition mean is compared with any other condition meano Problem is that there can be a lot of themo Not normally appropriate to conduct a statistical test on each pair of condition means b/c each involves a statistical test=more type 1 error- Complex comparisons- more than two means are compared at the same timeo Usually conducted with contrast tests- Post hoc comparisons- means comparisons that, by taking into consideration that many comparisons are being made and that these comparisons were not planned ahead of time, help control for increases in the experimentwise alphao Some cases they only allow the researchers to conduct them if the F test is significant- Planned (a priori) comparisons- compare only the means in which specific differences werepredicted by the research hypothesis5. Propose a 2 x 2 factorial experiment. Name the independent variables and the dependent variables, and label the levels of each. Predict an interaction, and state the expected form of this interaction. Draw a schematic diagram of the research hypothesis.Chapter 14: Quasi-Experimental Research Designs 104CHAPTER 12: EXPERIMENTAL CONTROL AND INTERNAL VALIDITYLEARNING OBJECTIVES1. Understand the potential threats to the validity of research.- Threats to construct validity- occurs when the measured variables used in the research are invalid because they do not adequately assess the conceptual variables they were designed to measure- Threats to statistical conclusion validity- occurs when the conclusions that the researcher draws about the research hypothesis are incorrect because either a Type 1 error or a Type 2 error has occurredo Type 1- researcher mistakenly rejects the nullo Type 2- researcher mistakenly fails to reject the null- Threats to internal validity- refers to the extent to which we can trust the conclusions that have been drawn about the causal relationship between the IV and DVo The DV may actually have been caused by a confounding variable- Threats to external validity- refers to the extent to which the results of a research design can be generalized beyond the specific settings and participants used in the experiment to other places, people and timeso Claims that results are more general, observed effects may actually only be found under limited conditions2. Define experimental control.- Occurs to the extent that the experimenter is able to eliminate effects of the DV other than the effects of the IV- The greater the experimental control, the more confident we can be that the IV caused the changes in the DV3. Determine the effects of extraneous variables on research validity.- Extraneous variables- variables other than the IV that cause changes in the DV- These aren’t measured by the experimenter, so their presence increases the within group variability- Makes it more difficult to find differences among the experimental conditions of the dependent measure4. Define confounding and understand how confounding reduces an experiment’s internal validity.- Confounding- means that the other variable is mixed up with the independent variable, making it impossible to determine which of the variables produced the change in the DV- Internal validity- extent to which changes in the DV can confidently be attributed to the effect of the IV, rather than to the potential effects of confounding variables- Internal validity is ensured only when there are no confounding variables5. Determine methods of controlling for extraneous variables in experimental research designs.- Limited population designs- select participants from a limited and therefore relatively homogeneous populationo Initial differences among participants constitute random errorChapter 14:
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