BHS Methods in Behavioral Sciences I

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Presentation transcript:

BHS 204-01 Methods in Behavioral Sciences I May 7, 2003 Chapter 6 (Ray) Threats to Validity

Sources of Variance Systematic variation – differences related to the experimental manipulation. Can also be differences related to uncontrolled variables (confounds) or systematic bias (e.g. faulty equipment or procedures). Chance variation – nonsystematic differences. Cannot be attributed to any factor. Also called “error”.

F-Ratio A comparison of the differences between groups with the differences within groups. Between-group variance = treatment effect + chance variance. Within-group variance = chance variance. If there is a treatment effect, then the between-group variance should be greater than the within-group variance.

Testing the Null Hypothesis Between-group variance (treatment effect) must be greater than within-group variance (chance variation), F > 1.0. How much greater? Normal curve shows that 2 SD, p <.05 is likely to be a meaningful difference. The p value is a compromise between the likelihood of accepting a false finding and the likelihood of not accepting a true hypothesis.

Box 6.1. (p. 135) Type I and Type II Errors.

Type I error – likelihood of rejecting the null when it is true and accepting the alternative when it is false (making a false claim). This is the p value -- .05 is probability of making a Type I error. Type II error – likelihood of accepting null when it is false and rejecting the alternative when it is true. Probability is b, the power of a statistic is 1-b.

Reporting the F-Ratio ANOVA is used to calculate the F-Ratio. Example: The experimental group showed significantly greater weight gain (M = 55) compared to the control group (M = 21), F(1, 12) = 4.75, p=.05. Give the degrees of freedom for the numerator and denominator.

When to Use ANOVA When there are two or more independent groups. When the population is likely to be normally distributed. When variance is similar within the groups compared. When group sizes (N’s) are close to equal.

Threats to Internal Validity It is the experimenter’s job to eliminate as many threats to internal validity as possible. Such threats constitute sources of systematic variance that can be confused with an effect, resulting in a Type I error. Potential threats to validity must be evaluated in the Discussion section of the research report.