MCQs For Lecturers
To be used in conjunction with Field, A. P., Miles, J., and Field, Z. C. (2012). Discovering
statistics using R: and sex and drugs and rock ’n’ roll. London: Sage. Questions are listed
under the chapter they best represent. Correct answers are denoted with a *.
Chapter 1
1. What is a confounding variable?
a. A variable that is manipulated by the experimenter.
b. A variable that affects the outcome being measured as well as or instead of
the independent variable.*
c. A variable that has not been measured.
d. A variable that is made up only of categories.
2. ‘Children can learn a second language faster before the age of 7’. Is this statement:
a. A null hypothesis.
b. A non‐scientific statement.
c. A two‐tailed hypothesis.
d. A one‐tailed hypothesis.*
3. If a psychological test is valid, what does this mean?
a. The test will give consistent results.
b. The test measures what it claims to measure.*
c. The test has internal consistency.
d. The test measures a psychologically useful variable.
4. If my null hypothesis is ‘Dutch people do not differ from English people in height’,
what is my alternative hypothesis?
a. Dutch people are taller than English people.
b. English people are taller than Dutch people.
c. Dutch people differ in height from English people.
d. All of the above are plausible alternative hypotheses.*
5. When questionnaire scores predict, or correspond with, external measures of the
same construct that the questionnaire measures it is said to have:
a. Ecological validity.
b. Factorial validity.
c. Content validity.
, d. Criterion validity.*
6. A variable manipulated by a researcher is known as:
a. A dependent variable.
b. A confounding variable.
c. A discrete variable.
d. An independent variable.*
7. A predictor variable is another name for:
a. A dependent variable.
b. A confounding variable.
c. A discrete variable.
d. An independent variable.*
8. What kind of variable is IQ, measured by a standard IQ test?
a. Categorical.
b. Discrete.
c. Nominal.
d. Continuous.*
9. A frequency distribution in which high scores are most frequent (i.e. bars on the
graph are highest on the right‐hand side) is said to be:
a. Positively skewed.
b. Leptokurtic.
c. Platykurtic.
d. Negatively skewed.*
10. A frequency distribution in which there are too few scores at the extremes of the
distribution is said to be:
a. Positively skewed.
b. Leptokurtic.*
c. Platykurtic.
d. Negatively skewed.
11. Which of the following is designed to compensate for practice effects?
a. A repeated measures design.
b. Randomization of participants.
c. Counterbalancing.*
d. A control condition.
12. Variation due to variables that have not been measured is known as:
, a. Unsystematic variance.*
b. Homogeneous variance.
c. Systematic variance.
d. Model variance.
13. If the scores on a test have a mean of 26 and a standard deviation of 4, what is the z‐
score for a score of 18?
a. –2*
b. 11
c. 2
d. –1.41
, Chapter 2
1. The degree to which a statistical model represents the data collected is known as
the:
a. Fit.*
b. Homogeneity.
c. Reliability.
d. Validity.
2. Which of the following is true about a 95% confidence interval for the mean of a
given sample:
a. 95 out of 100 sample means will fall within the limits of the confidence
interval.
b. There is a 95% chance that the population mean will fall within the limits of
the confidence interval.
c. 95 out of 100 confidence intervals will contain the population mean.*
d. There is a .05 probability that the population mean falls within the limits of
the confidence interval.
3. What is p the probability of?
a. p is the probability that the results are due to chance, the probability that the
null hypothesis (H0) is true.
b. p is the probability of observing results as extreme as (or more extreme than)
observed, if the null hypothesis (H0) is true.*
c. p is the probability that the results are not due to chance, the probability that
the null hypothesis (H0) is false.
d. p is the probability that the results would be replicated if the experiment was
conducted a second time.
4. A Type I error is when:
a. We conclude that there is an effect in the population when in fact there is
not.*
b. We conclude that there is not an effect in the population when in fact there
is.
c. We conclude that the test statistic is significant when in fact it is not.
d. The data we have entered into R is different than the data collected.
5. If we calculated an effect size and found it was r = .21, which expression would best
describe the size of effect?
a. Small.
b. Small to medium.*
To be used in conjunction with Field, A. P., Miles, J., and Field, Z. C. (2012). Discovering
statistics using R: and sex and drugs and rock ’n’ roll. London: Sage. Questions are listed
under the chapter they best represent. Correct answers are denoted with a *.
Chapter 1
1. What is a confounding variable?
a. A variable that is manipulated by the experimenter.
b. A variable that affects the outcome being measured as well as or instead of
the independent variable.*
c. A variable that has not been measured.
d. A variable that is made up only of categories.
2. ‘Children can learn a second language faster before the age of 7’. Is this statement:
a. A null hypothesis.
b. A non‐scientific statement.
c. A two‐tailed hypothesis.
d. A one‐tailed hypothesis.*
3. If a psychological test is valid, what does this mean?
a. The test will give consistent results.
b. The test measures what it claims to measure.*
c. The test has internal consistency.
d. The test measures a psychologically useful variable.
4. If my null hypothesis is ‘Dutch people do not differ from English people in height’,
what is my alternative hypothesis?
a. Dutch people are taller than English people.
b. English people are taller than Dutch people.
c. Dutch people differ in height from English people.
d. All of the above are plausible alternative hypotheses.*
5. When questionnaire scores predict, or correspond with, external measures of the
same construct that the questionnaire measures it is said to have:
a. Ecological validity.
b. Factorial validity.
c. Content validity.
, d. Criterion validity.*
6. A variable manipulated by a researcher is known as:
a. A dependent variable.
b. A confounding variable.
c. A discrete variable.
d. An independent variable.*
7. A predictor variable is another name for:
a. A dependent variable.
b. A confounding variable.
c. A discrete variable.
d. An independent variable.*
8. What kind of variable is IQ, measured by a standard IQ test?
a. Categorical.
b. Discrete.
c. Nominal.
d. Continuous.*
9. A frequency distribution in which high scores are most frequent (i.e. bars on the
graph are highest on the right‐hand side) is said to be:
a. Positively skewed.
b. Leptokurtic.
c. Platykurtic.
d. Negatively skewed.*
10. A frequency distribution in which there are too few scores at the extremes of the
distribution is said to be:
a. Positively skewed.
b. Leptokurtic.*
c. Platykurtic.
d. Negatively skewed.
11. Which of the following is designed to compensate for practice effects?
a. A repeated measures design.
b. Randomization of participants.
c. Counterbalancing.*
d. A control condition.
12. Variation due to variables that have not been measured is known as:
, a. Unsystematic variance.*
b. Homogeneous variance.
c. Systematic variance.
d. Model variance.
13. If the scores on a test have a mean of 26 and a standard deviation of 4, what is the z‐
score for a score of 18?
a. –2*
b. 11
c. 2
d. –1.41
, Chapter 2
1. The degree to which a statistical model represents the data collected is known as
the:
a. Fit.*
b. Homogeneity.
c. Reliability.
d. Validity.
2. Which of the following is true about a 95% confidence interval for the mean of a
given sample:
a. 95 out of 100 sample means will fall within the limits of the confidence
interval.
b. There is a 95% chance that the population mean will fall within the limits of
the confidence interval.
c. 95 out of 100 confidence intervals will contain the population mean.*
d. There is a .05 probability that the population mean falls within the limits of
the confidence interval.
3. What is p the probability of?
a. p is the probability that the results are due to chance, the probability that the
null hypothesis (H0) is true.
b. p is the probability of observing results as extreme as (or more extreme than)
observed, if the null hypothesis (H0) is true.*
c. p is the probability that the results are not due to chance, the probability that
the null hypothesis (H0) is false.
d. p is the probability that the results would be replicated if the experiment was
conducted a second time.
4. A Type I error is when:
a. We conclude that there is an effect in the population when in fact there is
not.*
b. We conclude that there is not an effect in the population when in fact there
is.
c. We conclude that the test statistic is significant when in fact it is not.
d. The data we have entered into R is different than the data collected.
5. If we calculated an effect size and found it was r = .21, which expression would best
describe the size of effect?
a. Small.
b. Small to medium.*
