Question

A clinical psychologist is studying the efficacy of a new drug medication for depression. The study includes a placebo group (no medication) versus a treatment group (new medication). He then measures the differences in depressive symptoms across the two groups.

What would a Type I error represent within the context of his study? How can he reduce the risk of committing a Type I error? How does this decision affect the risk of committing a Type II error?

Answer 1

Solution :

Assume,

H0: mu1-mu2=0 (there is difference in depression among two groups)

H1:mu1-mu2<0 (group1 has less depression than group 2)

Where, mu1 and mu2 represent new drug inflicted group and placebo group repectively.

The Type I error corresponds to rejecting a true null hypothesis, that is falsely concluding new drug inflicted group has lesser depression. Type II error corresponds to incorrect retention of false null hypothesis, that is falsely concluding that there is no difference n depression among the two groups.

There is no single way to reduce both Type I and Type II error together, but increasing sample size, will reduce the risk of Tpe I error.

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