In: Statistics and Probability
14. In formulating hypotheses for a statistical test of significance, the null hypothesis is often
a. a statement of “no effect” or “no difference.”
b. the probability of observing the data you actually obtained.
c. a statement that the data are all 0.
d. 0.05.
15. In assessing the validity of any test of hypotheses, it is good practice to
a. examine the probability model that serves as a basis for the test by using exploratory data analysis on the data.
b. determine exactly how the study was conducted.
c. determine what assumptions the researchers made.
d. all of the above.
16. In studies of worker productivity, it has been noticed that any change in the work environment together with knowledge that a study is underway will produce a short-term increase in productivity. This is known as
a. statistical significance.
b. the Hawthorne effect.
c. practical significance.
d. a critical value.
17. A Type II error is
a. rejecting the null hypothesis when it is true.
b. accepting the null hypothesis when it is false.
c. incorrectly specifying the null hypothesis.
d. incorrectly specifying the alternative hypothesis.
14. In formulating hypotheses for a statistical test of significance, the null hypothesis is often:
a. a statement of “no effect” or “no difference.”
15. In assessing the validity of any test of hypotheses, it is good practice to:
a. examine the probability model that serves as a basis for the test by using exploratory data analysis on the data.
b. determine exactly how the study was conducted.
c. determine what assumptions the researchers made.
Answer:- d. all of the above.
16. In studies of worker productivity, it has been noticed that any change in the work environment together with the knowledge that a study is underway will produce a short-term increase in productivity. This is known as:
c. practical significance.
17. A Type II error is:
b. accepting the null hypothesis when it is false.