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Chapter 8 – Lecture 6

Chapter 8 – Lecture 6. Hypothesis Question Initial Idea (0ften Vague) . Initial Observations. Search Existing Lit. . Statement of the problem. Operational definition of IV & DV. Research Hypothesis “If” “Then”. Research Hypotheses . Correlation:

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Chapter 8 – Lecture 6

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  1. Chapter 8 – Lecture 6

  2. Hypothesis Question Initial Idea (0ften Vague) Initial Observations Search Existing Lit. Statement of the problem Operational definition of IV & DV Research Hypothesis “If” “Then”

  3. Research Hypotheses Correlation: there is a significant correlation (+/-) between A & B Differential (quasi): there is a significant difference between A & B Experimental: Variable A will significantly affect variable B

  4. Design experiment to test your hypothesis Test the Null Hypothesis “Statistical Hypothesis” Alpha (0.05)  5% chance of differences btw groups due to chance (not a real difference) 5 times in 100 that difference is due to chance

  5. Experimentation (Hypothesis Testing) Threats to Validity is all about control - environment - undesirable and irrelevant factors could creep into your experiment and affect your results These factors are bad  “threatens” validity of results It is important to understand these threats when designing an experiment so you can try and avoid them “9 Evil Threats”

  6. Validity Are you measuring what you say you are measuring? METHODOLOGY! Methodological Soundness Anticipate potential threats to validity Create procedures to eliminate or reduce threats

  7. Types of Validity Statistical: accuracy of the conclusion drawn from a statistical test Construct: how well the results support the theory or construct (internal condition of exp) External: extent to which the results generalize (ecological validity) Internal: your study demonstrates that the experiment was the sole cause for a change in the dependent variable – vs other factors (threats) not related to the experiment

  8. Types of Validity Statistical: accuracy of the conclusion drawn from a statistical test Testing the Null Hypothesis (is the difference chance variation or the IV) Threats (1) measure used to measure DV is not reliable (2) violation of underlying statistical tests “assumptions” normality & homogeneity of variance

  9. Types of Validity Construct: how well the results support the theory or construct Hypothesis tested is gathered from theoretical ideas Threats (1) begin with a weak theory (2) rival theories not carefully ruled out

  10. Types of Validity External: generalization Major Threat: NO random assignment

  11. Types of Validity Internal: demonstration of causality Was it what you did that made the DV change or was it something else??? Did “A” cause “B” 9 Evil Threats to Internal Validity

  12. 1. History Changes to DV due to: Historical Event Ex: September 11th may have an effect on a study of patriotic behavior in college undergraduates Pre TX TX Post TX Compare Scores Single group pretest, Posttest Design

  13. 2. Maturation • Changes to DV due to: • natural processes in subjects • happen as a function of time • not as a function of the experiment • EX: aging, getting hungry, thirsty, more tired, etc. • Ex: filling out a 500-item questionnaire… • - get tired • - difficulty concentrating on answering items • - answers to items later in the test may be different from previous items, even if the items are similar

  14. 3. Instrumentation Changes to DV due to:some aspect of a measurement instrument or scale, or some change in an observer or scorer  Ex: an observer of children’s play behavior - more proficient over time affecting observation scores Ex: equipment - measure RT becomes less and less exact due to mechanical breakdown

  15. 4. Testing Changes to DV due to: taking a pre-test which may affect scores on the post-test Ex: IQ test scores - 3-5 points higher the second time - Reading test

  16. 5. Regression to the Mean Changes to DV due to: participants are selected because their scores on a measure are extreme (either high or low)…they will tend to be less extreme on a second testing (scores regress toward the mean some) Ex: Top 10% of a class – pretest shows they are above average….upon post test the change in score may not truly be due to your IV but due to the students score regressing toward the mean

  17. 6. Selection Changes to DV due to:groups being compared are not equivalent before manipulation begins Ex: comparing students identified by teachers as ‘extremely motivated’ vs control group - Recruited: $20 each - undesired effect of increasing motivation

  18. 7. Mortality Changes to DV due to: loosing subjects  can be death or not - you lose participants for Exp. or control groups for different reasons and/or you lose different numbers of participants in each group Ex: A clinical psychologist loses 40% of her Exp. Group but only 5% of the control group; the reason was because the “confrontation therapy” for the experimental group made clients too anxious to finish up treatment

  19. 8. Diffusion of TX Changes to DV due to: experimental groups communicating with each other – may give away the procedures …one group affects the other Ex: Dr. Suter’s experiment…one student tells another student what the experiment was about (contract effect..cow picture)…later the other student goes into the experiment knowing what is expected

  20. 9. Sequence Effects Changes to DV due to: the order in which the subjects receive treatments (repeated measures..within subs)…carry over effects Example: drugs…reading tests

  21. Also – threats to validity Subject effects: when people know they are being observed Changes to DV due to: demand characteristic cues given to subjects on how to behave in experiment (unintentional) Ex: placebo effect

  22. Chapter 9 How to control all these threats • General control procedures • Control over subject and experimenter effects • Control through participant selection and assignment • Control through specific experimental design

  23.  Preparation of setting – laboratory  Response Measurement - careful selection preparation of the instruments used to measure DV  Replication – “pilot data” • General control procedures •  Single & double blind procedures •  Automation: reduce experimenter/subject contact (tape recording etc) • Multiple observers:interrater reliability • Using deception: obscure the true hypothesis (vodka) 2. Control over subject & Experimenter effects

  24. 3. Control through subject selection & assignment •  Random sampling • Subject Assignment – random free random assigment (use random number table) matched random assigment – (age, weight) 4. Control over experimenter design  Simple Pretest-posttest design  Pretest-posttest , control group design

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