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Understanding Key Concepts in Experimental Psychology: Validity, Error Types, and Design

This lecture reviews essential concepts in experimental psychology, including confounding and extraneous variables, operational definitions, and the distinction between random sampling and random assignment. It explores internal validity, Type I and Type II errors, power in hypothesis testing, and the benefits of using multiple levels of an independent variable (IV) in research. Additionally, the lecture covers factorial designs, their advantages, and how to interpret main effects and interaction effects. Graphing techniques and naming conventions for design types are also discussed.

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Understanding Key Concepts in Experimental Psychology: Validity, Error Types, and Design

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  1. Lecture 13Psyc 300A

  2. Review • Confounding, extraneous variables • Operational definitions • Random sampling vs random assignment • Internal validity • Null hypothesis • Type I and type II errors

  3. Review: Confounding and extraneous variables • Extraneous variables can be confounds, but can also add variability (noise). For each, provide extraneous variable and confound: • Study 1: Effect of distraction on pain perception using cold immersion. • Study 2: Do girls benefit from sixth grade middle school?

  4. Review: Operational definitions • For each of the previous studies, operationalize the IV and DV

  5. Review: Random sampling vs random assignment • What is the difference between the two? • Random assignment is a way to prevent confounding

  6. Review: Internal validity • What is internal validity? • Internal validity: Ability to make valid inferences concerning the relationship between the IV and DV in an experiment. (effect on the DV is caused only by the IV)

  7. Type I and Type II Errors

  8. Power • Power is the probability of avoiding a Type II error. • Power is related to: • Alpha level • Effect size (mean and sd) • Number of participants

  9. Using More Than Two Levels of an IV • What is a level of an IV? • In an experiment with an experimental and control group, how many levels? • Can we have more than two levels? • Example: • Golf club study • Anxiety management techniques for speech-giving • Graphing the relationship

  10. Advantages of Multi-level Designs • Efficiency (fewer participants needed and less time) • Ability to see relationships better • Ex: Caffeine and Performance (0, 2, 4 cups of coffee)

  11. Graphing Relationships: One IV

  12. Multifactor Designs • Factorial design: A design in which all levels of each IV are combined with all levels of the other IVs. • Advantages of factorial designs: • More efficient (fewer participants and less experimenter time) • Allows us to see how variables interact

  13. Example: Movie Preferences

  14. What a Factorial Design Tells You • Main effect: The effect of an IV on the DV, ignoring all other factors in the study • Interaction effect: When the effect of one IV on a DV differs depending on the level of a second IV. • Graphing a factorial design • Interpreting the interaction first

  15. Examples of Main Effects and Interactions • A1= morning • A2= late afternoon • B1= high fat diet • B2= low fat diet • DV: 0-50 rating of energy level

  16. More Main Effects and Interactions • A1= morning • A2= late afternoon • B1= high fat diet • B2= low fat diet • DV: 0-50 rating of energy level

  17. More Main Effects and Interactions • A1= morning • A2= late afternoon • B1= high fat diet • B2= low fat diet • DV: 0-50 rating of energy level

  18. Group Activity: Main Effects and Interactions Make graphs of the following situations:

  19. Factorial Designs: Naming Conventions • The first number is the number of levels in first IV, second number is number of levels in second IV, etc. • 2 x 2 • 2 x 3 • 2 x 2 x 3 • Between-subjects, repeated measures (within), mixed

  20. A 2 x 3 Interaction

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