There is a greater risk of making which error with a directional ...

[colton]

There is a greater risk of making which error with a directional hypothesis?
 
  a. Concluding that there is a difference between groups when there really is no difference
  b. Concluding that there is no difference between groups when there is an inverse relationship
  c. Concluding that there is no difference between groups when there really is a difference
  d. Rejecting the null hypothesis when the measurement error is moderate

Question 2

Level of significance, sample size, power, and effect size are the four components of:
 
  a. decision theory.
  b. exploratory analysis.
  c. inference.
  d. power analysis.

[hanadaa]

Answer to Question 1

ANS: A
In a one-tailed test of significance, the hypothesis is directional. One-tailed statistical tests are uniformly more powerful than two-tailed tests, decreasing the possibility of a Type II error (saying there is no difference when there really is). This means the likelihood of a Type I error (saying there is a difference when there really is not) increases.
Concluding that there is no difference between groups when there is an inverse relationship is a Type II error.
Concluding that there is no difference between groups when there is an inverse relationship describes a Type II error.
Rejecting the null hypothesis when the measurement error is moderate would be true of both directional and nondirectional hypotheses.

Answer to Question 2

ANS: D
Cohen identified four parameters of a power analysis: the level of significance, sample size, power, and effect size.
The four components do not constitute decision theory.
Exploratory analysis is a preliminary step in the analysis of data.
Inference is the conclusion or judgment based on evidence.