Appendix C -- Supplemental Instructional Materials






COWI: Appendix C




SSRIC
Teaching Resources Depository

California Opinions on Women's Issues -- 1985-1995

Elizabeth N. Nelson and Edward E. Nelson, California State University,
Fresno


Appendix
C:

Supplemental Instructional Materials

©
The Authors
, 1998; Last Modified 15 August 1998

Reminder
on Reading Tables

  • Read the
    title carefully. (A good title tells exactly what is in the table.)
  • Look for
    headnotes or other explanations of the title.
  • Look for
    any footnotes. Do they apply to the whole table? If not, to what part?
  • Evaluate
    the source of the data. Is it likely to be reliable? Is it up to date?
  • Study the
    column and row headings. What do they mean?
  • Look for
    any overall average or total for the whole table. If the data are percentages,
    understand how they add to 100 percent.
  • Describe
    some of the numbers in words. (For example, [Number] percent of [100%]
    are [row or column heading].) Sometimes population numbers are given
    in thousands, so you need to remember that that means millions.
  • Look for
    patterns. What is the range? (For example, what are the largest and smallest
    percents?). Are most cases concentrated in one category, or are they more
    evenly spread out?
  • Summarize
    the main points of the table in words, using figures from the table as examples.

Table
C1 -- Marital Status* by Sex, March 1995

*Persons
age 18 and over

Marital
Status
Women
Men
Married
59.2
62.7
Widowed
11.1
2.5
Divorced
10.3
8.0
Never
Married
19.4
26.8
Total
(percent)
100.0
100.0
Total
(in thousands)
99,588
92,008
Source:
Bureau of the Census. 1996. Statistical Abstract of the United States:
1996. Washington DC: U. S. Government Printing Office. P.55

Sometimes it is
not obvious how a table adds to 100%. (See Table C2.) A quick examination shows
that it does not add to 100% down or across. (In 1890, 84% male + 18% female
would be more than 100%.) To save space, this chart omits the percent of people
who are not in the labor force. In 1890, the 84% of the males who were in the
labor force plus the 16% of the males who were not in the labor force equals
100%. Similarly, 18% of the females were in the labor force and the rest of
them were not in the labor force in 1890.

Table
C2 -- Labor Force Participation Rate* by Sex: 1890-1995

*Percent
of the noninstitutionalized population who are employed or who are
unemployed and looked for work in the last four weeks. (Pre-1947 figures
include those age 14 and over, later figures are age 16 and over).

Year Male Female
1890 84.3 18.2
1900 85.7 20.0
1920 84.6 22.7
1930 82.1 23.6
1940 82.5 27.9
1950 86.8 33.9
1955 86.2 35.7
1960 84.0 37.8
1965 81.5 39.3
1970 80.6 43.4
1975 78.4 46.4
1980 77.4 51.5
1985 76.3 54.5
1990 76.4 57.5
1995 75.0 58.9
Source:
U.S. Bureau of the Census. 1976. Historical Statistics of the United
States: Colonial Times to 1970.
(Bicentennial Ed.), Part I (1975),
Washington DC: U..S. Government Printing Office, pp 131-32; U.S. Bureau
of the Census. 1992. Statistical Abstract of the United States: 1992.
Washington DC: U.S. Government Printing Office, p 383; U.S. Bureau of
the Census. 1996. Statistical Abstract of the United States: 1996.Washington
DC: U.S. Government Printing Office, p.393.


Reminder and
Exercises

Frequency
and Percent Distributions, Figures and Graphs

Frequency and
percent distributions use only a few numbers to describe data.

Frequency
distributions
use charts to list the range of possible values and the
number of cases in each.

Percent distributions
convert the frequencies to percentages. (Remember that the percent is the
number per hundred, and the proportion is the part compared to the whole.
You may want to review basic math--fractions, decimals, and percents, perhaps
Overcoming Math Anxiety by Sheila Tobias or Where Do I Put the Decimal Point?
How to Conquer Math Anxiety and Increase your Facility with Numbers by Elisabeth
Ruedy and Sue Nirenbery.)

Exercise 1.a.

Construct a percent
distribution using the information from public opinion polls on women's issues
described in Chapter 2. Start with the percent who disapproved of a married
woman working if her husband could support her.

Tables should
have clear labels and definitions, so start your table with a title at the
top that describes exactly what it is. Label the columns and rows carefully.
Give the source of the data at the bottom of the table using one of the standard
reference formats such as those recommended by the American Sociological Association
or the American Psychological Association. (Note: Cite the source you used.
Give the original source, e.g., Yankelovich, only if you actually looked it
up and copied the figures from it. For this exercise, your source is Nelson,
Elizabeth and Ed Nelson. 1997. California Opinions on Women's Issues: 1985-1995.
Unpublished manuscript.)

Figures and
Graphs

We can present
the same information visually as figures or graphs.

Bar graphs
and Histograms
use rectangles to show the number or percent in each interval.
The intervals are marked along the horizontal axis (the bottom) and the frequencies
or percents along the vertical axis (the left side), so zero for both scales
is in the lower-left corner.

Histograms
are used with ordered, discrete or continuous data. Since age in years can
be ordered and is continuous from birth to old age, we would put the bars
right next to each other.

Bar graphs
use separate rectangles for each unit of nonordered, discrete data. For example,
marital status--married or single--cannot be quantified or ordered, so we
would use a separate bar for each category.

Frequency
Polygons
use dots at the midpoints of each interval in a similar way.
Notice that it would make sense to use a frequency polygon with ordered data
such as age but not for nonordered data such as race.

Exercise 1.b.

Construct a histogram
or bar chart using the same data as exercise 1.a. Remember that frequencies
or percents are usually marked along the left side of the chart with the smallest
numbers at the bottom and the values on the base start with the lowest values
and go from left to right so both scales use the same zero.

The overall impression
produced by a graph depends on the ratio of the measurements of the horizontal
and vertical scales. It is important to communicate these quantitative relationships
accurately. Experiment with different scales on scratch paper to find one
that seems to be a useful way to illustrate your data. Connect the midpoints
of the bars so you can see a frequency polygon. Again, be sure to use clear
labels. Usually the title of a figure or graph (called the legend) is on the
bottom. Include the source of your data in American Sociological Association
or American Psychological Association style.

Example with
Frequency Distribution, Percent Distribution, Dummy Table, and Crosstab

Frequency and
percent distributions use a few numbers to describe the data. Frequency
distributions
use charts to list the range of possible values and the
number of cases in each category. Percent distributions convert the
frequencies to percentages.

This example
comes from a study of opinions and behavior of California State University
Students in 1994. The question related to the students' knowledge of pregnancy
facts.

Table
C3 -- Frequency and Percent Distribution of CSU Students' Responses
to "At What Time in Her Monthly Cycle is a Woman Most Likely to become
Pregnant?" 
 
Number
Percent
Beginning
545
27.0
Middle
1,113
55.1
End
361
17.9
Total
2,019
100.0
Source:
Survey of California State University Students conducted by James Ross
(1994)

The percentages
show that over half (55%) of the CSU students answered the question correctly.
(A woman is most fertile in the middle of the monthly cycle.)

Crosstabulation

To analyze
means to break something down into its component parts and study them
in order to gain a better understanding of the whole. We can look at these
responses in more detail to gain a better understanding of students' knowledge
of this rather important part of human life. Crosstabulation uses tables
showing the number and percentage of cases in each combination of categories
of the data. We might expect that students would have better understanding
of health information related to their own bodies, so female students might
be more likely than the male students to answer correctly. So, we hypothesize
that females will be more likely to answer "middle." We can make a dummy table
showing what we would expect is the hypothesis were supported by the data.

Dummy
Table C4 -- Frequency and Percent Distribution of CSU Students' Responses
to "At What Time in Her Monthly Cycle is a Woman Most Likely to Become
Pregnant?" 
Male Female
Beginning a > b
Middle c < d
End e > f


The next table is
a crosstabulation of the responses by sex, so we can look at similarities and
differences in the responses of males and females. To crosstabulate by sex,
we construct separate frequency and percent distributions for each sex, calculating
the percentages down so we can compare across.

Table
C5 -- Frequency and Percent Distribution of CSU Students' Responses
to "At What Time in Her Monthly Cycle is a Woman Most Likely to Become
Pregnant?" by Sex
  Male Female Total
 
Number
Percent
Number
Percent
Number
Percent
Beginning
279
30.8
266
23.9
545
27.0
Middle
448
49.4
665
59.7
1,113
55.1
End
179
19.8
182
16.4
361
17.9
Total
906
100.0
1,113
100.0
2,019
100.0
Source:
Survey of California State University students conducted by James Ross
(1994)

Women students
were more likely than male students to answer correctly (60% of the women
compared to 50% of the men answered that a woman is most likely to become
pregnant in the middle of her monthly cycle).