INSTRUCTOR’S RESOURCE MANUAL
STATISTICS FOR PSYCHOLOGY
7TH EDITION
CHAPTER NO. 01: DISPLAYING THE ORDER IN A GROUP OF NUMBERS
USING TABLES AND GRAPHS
Learning Objectives
1–1 Understand and differentiate between descriptive and inferential statistics
1–2 Define basic statistical concepts
1–3 Display and clarify data using frequency tables
1–4 Create histograms and bar graphs from frequency tables
1–5 Identify the shape of a distribution of data
1–6 Consider the importance of how we measure variables
1–7 Understanding tables and graphs of frequency distributions in research articles
Instructor's Summary of Chapter
Difficulty of course: We have never had a student who could pass other college-level courses who could
not also pass this course—though, for many students, this course requires more work.
Reasons for psychology students to learn statistical methods: reading the psychology research
literature, conducting research, and developing analytic and critical thinking.
How to gain the most from this course: attend to the concepts (not just the numbers), master each
concept before going on to the next, keep up with reading and assignments, study intensely during the
first half of the course, and study with other students.
Descriptive statistics summarize and make understandable a group of numbers collected in a
research study.
, Inferential statistics make inferences about larger groups based on numbers from a particular
group of people studied.
Some basic concepts. Variables, values, and scores are differentiated.
Kinds of variables. Variables used in psychology are numeric (equal-interval), rank-order
(ordinal), or nominal (categorical). Sometimes, variables are also described as discrete or continuous.
Frequency tables organize the numbers into a table in which each of the possible values is listed
along the left from lowest to highest, accompanying each value by the number of cases and the
percentage of cases that have that value. Grouped frequency tables are used when there are a large
number of different values.
Histograms and bar graphs. A histogram is a graph in which the height of each bar represents the
frequency for a particular value. A bar graph is like a histogram except that it is used for nominal
variables, and there are spaces between the bars.
Distribution shapes. The general shape of a frequency distribution can be unimodal, bimodal,
multimodal, or rectangular; symmetrical or skewed (positive or negative); normal or kurtotic (peaked or
flat). The normal curve is bell-shaped, unimodal, and symmetrical.
Controversy: Measurement decisions. The choice that a researcher makes to measure a variable
can be controversial (e.g., nominal vs. continuous consideration of race) and will influence the type of
statistical tests that can be conducted.
How the procedures of this chapter are reported in research articles. When frequency tables
appear in research articles, it is usually in order to compare distributions and often involves frequencies
and percentages for various categories. Histograms rarely appear in articles, though the shapes of
distributions are occasionally described in words. Bar graphs, in contrast, often appear in research
articles.
Box 1-1. Important trivia for poetic statistics students. Summarizes the major historical sources
of statistical methods.
Box 1-2. Statistics anxiety, test anxiety, and you. Summarizes research and thinking on various
kinds of anxiety associated with studying statistics, plus methods for coping with these anxieties.
, Answers to Set II Practice Problems
This section only includes computations and related answers.
For examples of essays, graphs, etc., see Answers to Set I Practice Problems in the text.
Chapter 1
11 (a) number of words recalled; (b) 0 to 50; (c) 17
13 (a) X f %
1 2 10
2 4 20
3 8 40
4 4 20
5 2 10
14 (a) X f %
0 5 33.33
1 2 13.33
2 2 13.33
3 1 6.67
4 1 6.67
5 1 6.67
6 2 13.33
7 0 0.00
8 0 0.00
9 1 6.67
15 (a) Interval f %
15 – 19 1 2.50
20 – 24 3 7.50
25 – 29 2 5.00
30 – 34 15 37.50
35 – 39 11 27.50
40 – 44 4 10.00
45 – 49 2 5.00
50 – 54 2 5.00
16 (a) X f %
2 1 4
3 0 0
4 0 0
5 0 0
6 1 4
7 0 0
8 0 0
, 9 0 0
10 0 0
11 1 4
12 0 0
13 1 4
14 1 4
15 0 0
16 1 4
17 1 4
18 2 8
19 2 8
20 0 0
21 1 4
22 3 12
23 2 8
24 0 0
25 0 0
26 1 4
27 1 4
28 3 12
29 1 4
30 0 0
31 0 0
32 1 4
33 0 0
34 1 4
(b) Interval f %
0–4 1 4
5–9 1 4
10 – 14 3 12
15 – 19 6 24
20 – 24 6 24
25 – 29 6 24
30 – 34 2 8
STATISTICS FOR PSYCHOLOGY
7TH EDITION
CHAPTER NO. 01: DISPLAYING THE ORDER IN A GROUP OF NUMBERS
USING TABLES AND GRAPHS
Learning Objectives
1–1 Understand and differentiate between descriptive and inferential statistics
1–2 Define basic statistical concepts
1–3 Display and clarify data using frequency tables
1–4 Create histograms and bar graphs from frequency tables
1–5 Identify the shape of a distribution of data
1–6 Consider the importance of how we measure variables
1–7 Understanding tables and graphs of frequency distributions in research articles
Instructor's Summary of Chapter
Difficulty of course: We have never had a student who could pass other college-level courses who could
not also pass this course—though, for many students, this course requires more work.
Reasons for psychology students to learn statistical methods: reading the psychology research
literature, conducting research, and developing analytic and critical thinking.
How to gain the most from this course: attend to the concepts (not just the numbers), master each
concept before going on to the next, keep up with reading and assignments, study intensely during the
first half of the course, and study with other students.
Descriptive statistics summarize and make understandable a group of numbers collected in a
research study.
, Inferential statistics make inferences about larger groups based on numbers from a particular
group of people studied.
Some basic concepts. Variables, values, and scores are differentiated.
Kinds of variables. Variables used in psychology are numeric (equal-interval), rank-order
(ordinal), or nominal (categorical). Sometimes, variables are also described as discrete or continuous.
Frequency tables organize the numbers into a table in which each of the possible values is listed
along the left from lowest to highest, accompanying each value by the number of cases and the
percentage of cases that have that value. Grouped frequency tables are used when there are a large
number of different values.
Histograms and bar graphs. A histogram is a graph in which the height of each bar represents the
frequency for a particular value. A bar graph is like a histogram except that it is used for nominal
variables, and there are spaces between the bars.
Distribution shapes. The general shape of a frequency distribution can be unimodal, bimodal,
multimodal, or rectangular; symmetrical or skewed (positive or negative); normal or kurtotic (peaked or
flat). The normal curve is bell-shaped, unimodal, and symmetrical.
Controversy: Measurement decisions. The choice that a researcher makes to measure a variable
can be controversial (e.g., nominal vs. continuous consideration of race) and will influence the type of
statistical tests that can be conducted.
How the procedures of this chapter are reported in research articles. When frequency tables
appear in research articles, it is usually in order to compare distributions and often involves frequencies
and percentages for various categories. Histograms rarely appear in articles, though the shapes of
distributions are occasionally described in words. Bar graphs, in contrast, often appear in research
articles.
Box 1-1. Important trivia for poetic statistics students. Summarizes the major historical sources
of statistical methods.
Box 1-2. Statistics anxiety, test anxiety, and you. Summarizes research and thinking on various
kinds of anxiety associated with studying statistics, plus methods for coping with these anxieties.
, Answers to Set II Practice Problems
This section only includes computations and related answers.
For examples of essays, graphs, etc., see Answers to Set I Practice Problems in the text.
Chapter 1
11 (a) number of words recalled; (b) 0 to 50; (c) 17
13 (a) X f %
1 2 10
2 4 20
3 8 40
4 4 20
5 2 10
14 (a) X f %
0 5 33.33
1 2 13.33
2 2 13.33
3 1 6.67
4 1 6.67
5 1 6.67
6 2 13.33
7 0 0.00
8 0 0.00
9 1 6.67
15 (a) Interval f %
15 – 19 1 2.50
20 – 24 3 7.50
25 – 29 2 5.00
30 – 34 15 37.50
35 – 39 11 27.50
40 – 44 4 10.00
45 – 49 2 5.00
50 – 54 2 5.00
16 (a) X f %
2 1 4
3 0 0
4 0 0
5 0 0
6 1 4
7 0 0
8 0 0
, 9 0 0
10 0 0
11 1 4
12 0 0
13 1 4
14 1 4
15 0 0
16 1 4
17 1 4
18 2 8
19 2 8
20 0 0
21 1 4
22 3 12
23 2 8
24 0 0
25 0 0
26 1 4
27 1 4
28 3 12
29 1 4
30 0 0
31 0 0
32 1 4
33 0 0
34 1 4
(b) Interval f %
0–4 1 4
5–9 1 4
10 – 14 3 12
15 – 19 6 24
20 – 24 6 24
25 – 29 6 24
30 – 34 2 8
