Statistics for the Behavioral Sciences Second Edition Chapter 6: The Normal Curve, Standardization, and z Scores iClicker Questions Copyright © 2012 by.

Statistics for the Behavioral SciencesSecond Edition

Chapter 6:

The Normal Curve, Standardization, and z Scores

iClicker Questions

Copyright © 2012 by Worth Publishers

Susan A. Nolan and Thomas E. Heinzen

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.

Chapter 6

Chapter 6 (Answer)

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.

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.

Chapter 6 (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.

3. 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.

Chapter 6

3. 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.

Chapter 6 (Answer)

Chapter 64. When transforming raw scores into z scores, the formula is: a) (μ – X)

Z= ___________

Σ

b) (X – μ)

Z= __________

σ

c) (∑ – X)

Z= __________

Σ

  d) (X – σ)

Z= _________

S

Chapter 6 (Answer)4. When transforming raw scores into z scores, the formula is: a) (μ – X)

Z= ___________

Σ

b) (X – μ)

Z= __________

σ

c) (∑ – X)

Z= __________

Σ

  d) (X – σ)

Z= _________

S

Chapter 6

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?

a) -2.6

b) 1.6

c) -2.3

d) 1.3

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?

a) -2.6

b) 1.6

c) -2.3

d) 1.3

Chapter 6 (Answer)

Chapter 6

6. The mean of a z distribution is always:

a) 1.

b) 0.

c) 10.

d) 100.

Chapter 6 (Answer)

6. The mean of a z distribution is always:

a) 1.

b) 0.

c) 10.

d) 100.

Chapter 6

7. A normal distribution of standardized scores is called the:

a) standard normal distribution.

b) null distribution.

c) z distribution.

d) sample distribution.

Chapter 6 (Answer)

7. A normal distribution of standardized scores is called the:

a) standard normal distribution.

b) null distribution.

c) z distribution.

d) sample distribution.

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.

Chapter 6

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.

Chapter 6 (Answer)

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.

Chapter 6 (Answer)

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.

Chapter 6 10. The standard deviation of a distribution of means is

called the:

a) standard score.b) standard error.c) central limit theorem.d) normal curve.

Chapter 6 (Answer)

10. The standard deviation of a distribution of means is called the:

a) standard score.b) standard error.c) central limit theorem.d) normal curve.

Chapter 6

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.

Chapter 6 (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.