BHS 204-01 Methods in Behavioral Sciences I May 9, 2003 Chapter 6 and 7 (Ray) Control: The Keystone of the Experimental Method.

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Presentation transcript:

BHS Methods in Behavioral Sciences I May 9, 2003 Chapter 6 and 7 (Ray) Control: The Keystone of the Experimental Method

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.

Types of 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 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 , the power of a statistic is 1- .

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.

Two Ways of Achieving Control  Participant assignment and selection: Random sampling. Random assignment to conditions.  Experimental design: Add a control group. Include a baseline measurement before the treatment (pretest). Treat subjects consistently across all groups. Four-group design tests for effects of the testing.

Figure 7.3. (p. 159) The four conceptual steps in experimentation.