Understanding Psychology (10th Ed)

E VA LU AT E
1.
A frequency distribution of numbers could be displayed 
pictorially by constructing a bar graph, or 
.
statistics p. A-5
descriptive statistics p. A-5
frequency distribution p. A-5
histogram p. A-5
central tendency p. A-6
mean p. A-6
median p. A-7
mode p. A-7
normal distribution p. A-8
2.
Match each item in the left-hand column with the corre-
sponding item in the right-hand column.
1.
Mean 
5
10
a.
2, 8, 10, 12, 13, 18
2.
Median 
5
11
b. 4, 5, 10, 10, 15, 16
3. Mode 
5
12
c.
4, 5, 12, 12, 12, 16
3.
The mean, median, and mode are measures of 
.
4. Professor Garcia explains to the class that most of the 
40 exam scores fell within a B range, but there were two 
extremely high scores. Should she report the median or 
the mean as a measure of central tendency?
5. The mean, median, and mode will differ in a normal dis-
tribution. True or false?
R E T H I N K
1. Government statistics on family income are presented in a 
variety of ways. What would be the most useful way of 
providing a summary of family incomes across the coun-
try: the mean, median, or mode? Why might providing 
only the mean be misleading?
Answers to Evaluate Questions
1.
histogram; 2.
1-b, 2-a, 3-c; 
3. central tendency; 
4. the median; the 
mean is too sensitive to extreme scor
es; 5.
false; they will be equal 
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A-10
Although measures of central tendency provide information about where the center 
of a distribution lies, often this information is insuffi cient. For example, suppose a 
psychologist was interested in determining the nature of people’s eye movements 
while they were reading in order to perfect a new method to teach reading. It would 
not be enough to know how most people moved their eyes (information that a mea-
sure of central tendency would provide); it would also be important to know how 
much individual people’s eye movements differed or varied from one another. 
A second important characteristic of a set of scores provides this information: 
variability. Variability is a term that refers to the spread, or dispersion, of scores in 
a distribution. Figure 1 contains two distributions of scores that have identical means 
but differ in variability. Measures of variability provide a way to describe the spread 
of scores in a distribution.