Statistics for the Behavioral Sciences by Frederick J. Gravetter, Larry B. Wallnau ISBN 10: 1305504917 ISBN 13: 9781305504912

SUMMARY 125
2. A population has a mean of m 5 35 and a standard deviation of s 5 5. After 3 points
are added to every score in the population, what are the new values for the mean and
standard deviation?
a. m 5 35 and s 5 5
b. m 5 35 and s 5 8
c. m 5 38 and s 5 5
d. m 5 38 and s 5 8
3. What symbols are used for the mean and standard deviation for a sample in a
research report?
a. The mean is identified by the letter M and the standard deviation is represented
by a lowercase s.
b. The mean is identified by the letter M and the standard deviation is represented
by SD.
c. The mean is identified by a lowercase letter m and the standard deviation is
represented by a lowercase s.
d. The mean is identified by a lowercase letter m and the standard deviation is
represented by SD.
4. Under what circumstances would a score that is above the mean by 5 points appear
to be very close to the mean?
a. When the mean is much greater than 5
b. When the mean is much less than 5
c. When the standard deviation is much greater than 5
d. When the standard deviation is much less than 5
5. For which of the following pairs of distributions would the mean difference be
easiest to see?
a. M 5 45 with s 5 5 compared to M 5 50 with s 5 5.
b. M 5 45 with s 5 5 compared to M 5 55 with s 5 5.
c. M 5 45 with s 5 10 compared to M 5 50 with s 5 10.
d. M 5 45 with s 5 10 compared to M 5 55 with s 5 10.
ANSWERS
1. D, 2. C, 3. B, 4. C, 5. B
SUMMARY
1. The purpose of variability is to measure and describe
the degree to which the scores in a distribution are
spread out or clustered together. There are three basic
measures of variability: the range, variance, and standard
deviation.
The range is the distance covered by the set of
scores, from the smallest score to the largest score.
The range is completely determined by the two
extreme scores and is considered to be a relatively
crude measure of variability.
Standard deviation and variance are the most commonly
used measures of variability. Both of these
measures are based on the idea that each score can be
described in terms of its deviation or distance from the
mean. The variance is the mean of the squared deviations.
The standard deviation is the square root of the
variance and provides a measure of the standard distance
from the mean.
2. To calculate variance or standard deviation, you first
need to find the sum of the squared deviations, SS.