Multiple choice questions

Quizzes are available to test your understanding of the key concepts covered in each chapter. Click on the quiz below to get started.

1.    Classify each of the following statements about statistical power as either true or false. 

  1. Power is the ability of a test to detect an effect given that an effect of a certain size exists in a population. 
  2. We can use power to determine how large a sample is required to detect an effect of a certain size.
  3. Power is linked to the probability of making a Type II error.
  4. The power of a test is the probability that a given test is reliable and valid.

(Hint: The power of a test is the probability that a given test will find an effect assuming that one exists in the population.)

The correct answer is a) true b) true c) true d) false

2.    Classify each of the following statements about statistical power as either true or false. The power of a statistical test depends on:

  1. How big the effect actually is. 
  2. How strict we are about deciding that an effect is significant.
  3. The sample size.
  4. Whether the test is a one- or two-tailed test.

(Hint: The power of a test is the probability that a given test will find an effect assuming that one exists in the population.)

The correct answer is a) true b) true c) true d) true

3.    Imagine you conducted a study to look at the association between whether an expectant mother eats breakfast (or not) and the gender of her baby. Cramér’s V = .22. How would you interpret this value? 

(Hint: Cramér’s V can range between 0 and 1.)

  1. There is a medium to large association between the gender of the baby and whether or not the mother ate breakfast every day.
  2. There was a small to medium association between baby gender and whether the mother ate breakfast every day.
  3. 22% of the variation in frequency counts of baby gender (boy or girl) can be explained by whether or not the mother ate breakfast every day.
  4. 2.2% of the variation in frequency counts of baby gender (boy or girl) can be explained by whether or not the mother ate breakfast every day.

The correct answer is b) There was a small to medium association between baby gender and whether the mother ate breakfast every day.

4.    In logistic regression, what is the R-statistic?

  1. It is the partial correlation between the outcome variable and each of the predictor variables.
  2. It is the semi-partial correlation between the outcome variable and each of the predictor variables.
  3. It is the polychoric correlation between the outcome variable and each of the predictor variables.
  4. It is the correlation between the outcome variable and each of the predictor variables.

The correct answer is a) It is the partial correlation between the outcome variable and each of the predictor variables. This is because a positive value indicates that as the predictor variable increases, so does the likelihood of the event occurring. A negative value implies that as the predictor variable increases, the likelihood of the outcome occurring decreases.