This situation is probably the most common experimental design in Psychology. These designs are sometimes called between-subjects or between-groups designs.
Once again, the generic formula for the T-Statistic is:
For the Independent Samples T-Statistic:
The data report for the ViSta Data is:
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The ViSta Applet for these data yields the following workmap:
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We analyze these data using a one-tailed test based on a directional hypothesis that the directed reading activity will improve reading ability scores (that the "Treatment" group will have higher scores than the "Control" group).
Report-Model: The analysis of these data produces the following model report:
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Visualize-Model: As pointed out in the chapter, the significance test requires that the data come from populations that are normally distributed with equal variance. The visualization helps us see whether these assumptions are met.
Normality: Interpreting features of these plots discussed above, we conclude that the data are reasonably normal.
Equal Variance: The box-plot, however, reveals that there may be more variation in the control group than in the treatment group (the box for the control group is taller than for the treatment group, and the observation dots cover a wider range for the control group). This may mean that the value of p (.0129) may be too optimistic. We note that we have one outlying control group value. Perhaps we should remove it and reanalyze the data.