1. Statistics for the Behavioral Sciences
Susan A. Nolan and Thomas E. Heinzen
Statistics for the Behavioral Sciences
Second Edition
Chapter 6:
The Normal Curve, Standardization, and z Scores
iClicker Questions
Copyright © 2012 by Worth Publishers

2. Chapter 6 1. All of the following are true of the normal curve EXCEPT:
a) it is bell-shaped.
b) it is unimodal.
c) it has an inverted U shape.
d) it is symmetric.

3. Chapter (Answer)
All of the following are true of the normal curve EXCEPT:
a) it is bell-shaped.
b) it is unimodal.
c) it has an inverted U shape.
d) it is symmetric.

4. Chapter 6
2. A normal distribution of scores will more closely resemble a normal curve as:
a) the sample size increases.
b) the sample size decreases.
c) more outliers are added to the sample.
d) scores are converted to z-scores.

5. Chapter (Answer)
2. A normal distribution of scores will more closely resemble a normal curve as:
a) the sample size increases.
b) the sample size decreases.
c) more outliers are added to the sample.
d) scores are converted to z-scores.

6. Chapter 6 A z score is defined as the: a) mean score.
b) square of the mean score.
c) square root of the mean score divided by the mean.
d) number of standard deviations a particular score is from the mean.

7. Chapter 6 (Answer) A z score is defined as the: a) mean score.
b) square of the mean score.
c) square root of the mean score divided by the mean.
d) number of standard deviations a particular score is from the mean.

8. Chapter 6 When transforming raw scores into z scores, the formula is:
a) (μ – X)
Z= ___________ Σ
b) (X – μ)
Z= __________ σ
c) (∑ – X)
  d) (X – σ)
Z= _________ S

9. Chapter (Answer)
When transforming raw scores into z scores, the formula is:
a) (μ – X)
Z= ___________ Σ
b) (X – μ)
Z= __________ σ
c) (∑ – X)
  d) (X – σ)
Z= _________ S

10. Chapter 6
Matthew recently took an IQ test in which he scored an IQ of 120. If the population’s mean IQ is 100 with a standard deviation of 15, what is Matthew’s z score?
-2.6
1.6
c) -2.3
d) 1.3

11. Chapter (Answer)
5. Matthew recently took an IQ test in which he scored an IQ of 120. If the population’s mean IQ is 100 with a standard deviation of 15, what is Matthew’s z score?
-2.6
b) 1.6
c) -2.3
d) 1.3

12. Chapter 6 The mean of a z distribution is always: a) 1. b) 0. c) 10.

13. Chapter 6 (Answer) The mean of a z distribution is always: a) 1. b) 0.

14. Chapter 6 A normal distribution of standardized scores is called the:
a) standard normal distribution.
b) null distribution.
c) z distribution.
d) sample distribution.

15. Chapter (Answer)
A normal distribution of standardized scores is called the:
a) standard normal distribution.
b) null distribution.
c) z distribution.
d) sample distribution.

16. Chapter 6
The assertion that a distribution of sample means approaches a normal curve as sample size increases is called:
a) Bayes theorem.
b) the normal curve.
c) De Moivre’s theorem.
d) the central limit theorem.

17. Chapter (Answer)
8. The assertion that a distribution of sample means approaches a normal curve as sample size increases is called:
a) Bayes theorem.
b) the normal curve.
c) De Moivre’s theorem.
d) the central limit theorem.

18. Chapter 6
9. How is a distribution of means different from a distribution of raw scores?
a) The distribution of means is more tightly packed.
b) The distribution of means has a greater standard deviation.
c) The distribution of means cannot be plotted on a graph.
d) All of the above are true.

19. Chapter (Answer)
How is a distribution of means different from a distribution of raw scores?
a) The distribution of means is more tightly packed.
b) The distribution of means has a greater standard deviation.
c) The distribution of means cannot be plotted on a graph.
d) All of the above are true.

20. Chapter 6
The standard deviation of a distribution of means is called the:
a) standard score.
b) standard error.
c) central limit theorem.
d) normal curve.

21. Chapter (Answer)
The standard deviation of a distribution of means is called the:
a) standard score.
b) standard error.
c) central limit theorem.
d) normal curve.

22. Chapter 6
Statisticians can use principles based on the normal curve to:
a) catch cheaters.
b) encourage people to conform to expected behavior.
c) remove unwanted scores from the data set.
d) detect confounds in an experiment.

23. Chapter (Answer)
11. Statisticians can use principles based on the normal curve to:
a) catch cheaters.
b) encourage people to conform to expected behavior.
c) remove unwanted scores from the data set.
d) detect confounds in an experiment.