PSYC2030 Exam Review #2

1. PSYC2030Exam Review #2 March 13th 2014

2. Chapter 5

3. Essential Features of Experimental Research • What is an independent variable and what is meant by the term “levels” of an independent variable? • Independent variable: • The factor of interest to the researcher • Must have a minimum of two levels (Situations/Conditions) • Can be manipulated by the experimenter • E.g., experimentally eliciting anxiety in Group A but not in Group B • Participants can be selected based on their attributes • E.g., selecting two groups that differ in anxiety level

4. Essential Features of Experimental Research • Distinguish between an experimental and a control group. • Experimental group: • Receives treatment • Control group: • Treatment is withheld • = comparison group

5. Essential Features of Experimental Research • What is a confounding variable and why is it a problem in experimental research? • Confounding variable: • Any uncontrolled extraneous variable that covaries with the independent variable and could provide an alternative explanation of the results • Problem? • Difficult to interpret results • Results could be due to the effect of the independent variable, confounding variable, or some combination of both

6. Essential Features of Experimental Research • In psychological research, what is a dependent variable? • Behaviour measured as an outcome of an experiment • If we study the effect of X on Y • X = Independent Variable • Y = Dependent Variable

7. Essential Features of Experimental Research • What is the difference between a ceiling and a floor effect? • Ceiling effect • The average score in both groups is so high that no difference can be determined • E.g., questions are too easy • Floor effect • The average score in both groups is so lowthat no difference can be determined • E.g., questions are too difficult

8. Manipulated versus Subject Variables • What is meant by a subject variable? Give two examples. • Subject variable: Existing characteristics of the individual participating in the study • Examples • Sex • Age • Socioeconomic status

9. Manipulated versus Subject Variables • When drawing conclusions from studies using manipulated variables, statements about cause can be made. These statements cannot be made when using subject variables. Why? • With manipulated variables, groups are created based on random assignment • The researcher can be fairly confident that the groups are are equal (i.e., any differences will be random) • With subject variables, groups are created based on participants’ characteristics • The researcher can’t be certain that the groups are equal (i.e., differences might not be random) • Any differences might be due to individual differences than covary with the subject variables

10. The Validity of Experimental Research • Give two examples of mistakes that result in a loss of statistical conclusion validity. • What is statistical conclusion validity? • The extent to which the researcher uses statistics properly and draws the appropriate conclusions from the statistical analysis • Examples of mistakes: • Using the wrong analysis technique or violate some of the assumptions required for performing a particular analysis • Reporting some results but not others

11. The Validity of Experimental Research • Distinguish internal from external validity. • Internal validity: the degree to which an experiment is methodologically sound and confound-free • External validity: the degree to which research findings generalize beyond the specific experiment being conducted

12. Threats to Internal Validity • How might attrition reduce an experiment’s internal validity? • Attrition: participants leaving the study over the course of time • Problem? • The group finishing the study is made up of different types of people than is the group that started the study.

13. Threats to Internal Validity • Distinguish between testing and instrumentation as threats to the internal validity of a study. • Testing: Occurs when the fact of taking a pretest influences posttest scores (perhaps by sensitizing participants to the purpose of the study) • Instrumentation: Occurs when the measuring instrument changes from the pretest to the posttest

14. Chapter 6

15. Between-Subjects Designs • In a between-subjects design, why is it important to aim for equivalent groups? • Between subjects design: an experimental design in which different groups of participants serve in the different conditions of the study • we want to make sure that any differences between the groups is due to the levels of the independent variable

16. Between-Subjects Designs • Other than the problem of equivalent groups, what is a disadvantage of using a between-subjects design? • Large numbers of people may be need to be recruited, tested, and debriefed during the course of the study

17. The Problem of Creating Equivalent Groups • What is the difference between random selection and random assignment? • Random selection: A procedure for getting volunteers to come into your study. Every person has an equal chance to participating. • Random assignment: A procedure to assign participants to conditions. Every person participating has an equal chance of bring placed in any of the conditions/groups in the study.

18. The Problem of Creating Equivalent Groups • Explain how random assignment accomplishes the goal of creating equivalent groups • Individual differences are randomly spread out across conditions

19. The Problem of Creating Equivalent Groups • Explain how simple random assignment differs from blocked random assignment • With simple random assignment, there is no guarantee that the groups will be equal in size (e.g., flipping a coin 20 times can result in heads all 20 times) • With blocked random assignment, participants are assigned to blocks of alternating conditions

20. Within-Subjects Designs • What are the advantages of within-subjects designs over between-subjects designs? • Within-subjects designs: an experimental design in which the same participants serve in each of the conditions of the study • Advantage over between-subjects designs? • Fewer people are required! • Eliminate the equivalent groups problem

21. Within-Subjects Designs • What is the main problem that a within-subjects design has to solve? • Order effect: the experience of participating in one condition of the study influences performance in subsequent conditions

22. Within-Subjects Designs • What is the difference between a progressive effect and a carryover effect? • Progressive effect: performance changes steadily from trial to trial (e.g., fatigue) • Carryover effect: performance changes as a result of one sequence of events rather than another (e.g., easy-difficult Qs vs. difficult-easy Qs)

23. The Problem of Controlling Sequence Effects • What is the general purpose of counterbalancing? • The order of conditions/presentation is randomized for each subject, thus eliminating order effects

24. The Problem of Controlling Sequence Effects • what is “complete” counterbalancing? If there are five different conditions in a study, how many sequences will be needed if complete counterbalancing is going to be used? • complete counterbalancing occurs when all possible orders are used • Five conditions: 5! = 120 sequences

25. The Problem of Controlling Sequence Effects • What is “partial” counterbalancing? What are two ways to accomplish partial counterbalancing? • Partial counterbalancing: a subset of all possible orders of conditions is used • Sampling from the complete set of all possible orders • Randomizing the order of conditions for each subject

26. Control Problems in Developmental Research • What is a cross-sectional design? • In developmental psychology, a design in which age is the independent variable and different groups of people are tested • Each group is of different age

27. Control Problems in Developmental Research • What are cohort effects and how might they make the interpretation of cross-sectional designs difficult? • Cohort: group of people born at the same time • Cohort effects: differences between groups are due to growing up in different historical times

28. Control Problems in Developmental Research • What is a longitudinal design? • In developmental psychology, a design in which age is the independent variable and the same group of people is being tested repeatedly at different ages

29. Control Problems in Developmental Research • Describe how a cohort sequential design combines elements of cross-sectional and longitudinal designs • A new cohort is added to a study every few years and then studied periodically throughout the time course of the study • Attempts to balance cohort and attrition problems

30. Problems with Biasing • What is experimenter bias and how can it be demonstrated experimentally? • Occurs when an experimenter’s expectations about a study affect its outcome

31. Problems with Biasing • What are two ways to control experimenter bias? • Research protocols: detailed descriptions of of the sequence of events in a research session • Ensures uniformity of treatment of research participants • A double blind procedure: neither the participant nor the experimenter knows which condition of study is being tested

32. Problems with Biasing • What is the Hawthorne effect? • A form of participant bias in which a participant’s behaviour is influenced by the mere knowledge of being in an experiment and therefore important to the experimenter

33. Problems with Biasing • What is the good subject effect, how does it relate to demand characteristics, and how might it influence the outcome of a study? • Good subject effect: A form of participant bias in which participants try to guess the experimenter’s hypothesis and then behave in such a way to confirm it • Demand characteristics: A feature of the experimental design that increases the chance that participants will detect the true purpose of the study

34. Problems with Biasing • How can participant bias be controlled? • Reduce demand characteristics • Deception • Placebo control group • Manipulation check: • Asks participants what they thought the study was about • Checks for the presence of demand characteristics • Conduct field research

35. Chapter 7

36. Single-Factor – Two Levels • Describe the Stroop effect and explain why his first two studies were examples of single factor repeated-measures designs. • Single factor design: An experimental design with a single independent variable • Stroop effect: When the name of a color is printed in a color that doesn’t match the name, naming the color of the word takes longer and is more prone to errors than when the color of the ink matches the name of the color

37. Single-Factor – Two Levels • Identify the situations when a t test for independent samples will be used and when a t test for related samples will be used. • Independent t-test • Used when two groups are completely independent from one another • Random assignment • Subject variables with two groups (males vs. females) • Dependent samples t-test: • Matched groups design • Repeated-measures designs

38. Presenting Data • There are Three Ways: • 1. Numbers can be presented in sentence form • 2. Construct a table of results • 3. Graphical Representation

39. Presenting Data • • How you present your data depends on the type of IV you are interested in...  Continuous Data: Use a line graph, but a bar graph is adequate  Discrete Data: Use a bar graph, line graph is inappropriate.  The IV is always presented on the X axis or the horizontal line  The DV is always presented on the Y axis or vertical line

40. Control Group Designs • What is a placebo and what is the reason for including a placebo control group in an experiment? • Placebo: a substance given to a participant in a form suggesting a specific pharmacological effect when in fact the substance in inactive • Purpose? Sometimes effect is caused simply by believing in the drug.

41. Control Group Designs • Placebo Control Groups: Participants are led to believe they are expecting some treatment when they are actually not. This type of control group is often used in pharmacological studies

42. Control Group Designs • Waitlist Control Groups: Often used to assess the effectiveness of the program and helps eliminate alternative explanations for the results you obtain such as general improvement because of passage of time

43. Control Group Designs • Yoked Control Groups: when each member of the control group is matched or “yoked” to a member of the experimental group so that the amount of time spent participating in the events in each condition is equivalent across your groups.