Use the following GSS data on race, fear, and home ownership to do the following:
| Respondent | Race |
Fear of Walking Alone |
Rent/Own |
| 1 | White |
No |
Rent |
| 2 | Black |
No |
Rent |
| 3 | White |
Yes |
Rent |
| 4 | Black |
No |
Rent |
| 5 | White |
No |
Rent |
| 6 | Black |
Yes |
Own |
| 7 | White |
Yes |
Rent |
| 8 | White |
Yes |
Rent |
| 9 | White |
No |
Own |
| 10 | White |
No |
Own |
| 11 | White |
Yes |
Rent |
| 12 | White |
No |
Rent |
| 13 | Black |
Yes |
Own |
| 14 | White |
No |
Rent |
| 15 | Black |
No |
Own |
| 16 | Black |
No |
Rent |
| 17 | White |
No |
Own |
| 18 | White |
No |
Own |
| 19 | Black |
No |
Rent |
| 20 | White |
No |
Own |
| 21 | Black |
Yes |
Rent |
Construct a bivariate table of frequencies for race and fear of walking alone at night.
|
Race Fear of Walking Alone |
|||
|
W |
B |
Total |
|
|
Y |
4 |
3 |
7 |
|
N |
9 |
5 |
14 |
|
Total |
13 |
8 |
21 |
Delegate your assignment to our experts and they will do the rest.
Calculate percentages for this table.
White:
Black:
|
Race Fear of Walking Alone |
||
|
W |
B |
|
|
Y |
57% |
43% |
|
N |
64% |
36% |
Describe the existence and the strength of the relationship between race and fear of walking alone based on this table.
Based on the table, it is evident that 57% of the people who fear walking alone at night while and 43% are blacks. From the same table, 64% of the people who do not fear walking alone are white and 36% are blacks. However, since the sample sizes are small, there are small sample biases in concluding anything.
Construct a bivariate table (using percentages) to compare fear of walking alone at night between people who own their homes and those who rent.
|
Ownership Fear of Walking Alone |
|||
|
Rent |
Own |
Total |
|
|
Y |
5 |
2 |
7 |
|
N |
8 |
6 |
14 |
|
Total |
13 |
8 |
21 |
|
Ownership Fear of Walking Alone |
||
|
Rent |
Own |
|
|
Y |
38% |
25% |
|
N |
62% |
75% |
Describe the existence and the strength of the relationship between fear of walking alone at night and people who own their homes and those who rent based on this table.
From the table, 38% of people who stay in a rented house fear walking alone at night and 25% of people of people who stay in their own houses fear walking alone. Also, 62% of people who stay in rented house do not fear walking alone at night and 75% of people who stay in their own house do not fear walking alone at night.
We want to find out whether there is a gender difference in general attitudes about crime and punishment. The General Social Survey (GSS) asks respondents whether they think courts are too harsh, about right, or not harsh enough in dealing with criminal offenders. The following table contains the data.
| Attitude Toward Courts |
Sex |
Total |
|
|
Male |
Female |
||
|
Too harsh |
134 |
135 |
269 |
|
About right |
173 |
207 |
380 |
Not harsh enough |
498 |
630 |
1,128 |
|
Total |
805 |
972 |
N = 1,777 |
Identify variables.
Independent: Sex
Dependent: Attitude towards courts
Percentage the table.
| Attitude Toward Courts |
Sex |
Total |
|
|
Male |
Female |
||
|
Too harsh |
16.7% |
13.9% |
15.1% |
|
About right |
21.5% |
21.3% |
21.4% |
Not harsh enough |
61.9% |
64.8% |
63.5% |
|
Total |
100% |
100% |
100% |
What percentage of those polled think that the courts are not harsh enough?
63.5% of those polled think that the courts are not harsh enough.
Using the percentaged table, describe the existence and strength of the relationship between gender and attitudes about crime and punishments.
From the table, 16.7% of men and 13.9% of women polled think that the courts are too harsh. 21.5% of men and 21.3% of women polled think that the courts are about right. 61.9% of men and 64.8% of women polled think that the courts are not harsh enough. A total of 15.1%, 21.4%, and 63.5% think that the courts are too harsh, about right and not too harsh respectively.
Calculate the chi-square statistic for this table.
| Attitude Toward Courts |
Sex |
Total |
|
|
Male |
Female |
||
|
Too harsh |
134 |
135 |
269 |
|
About right |
173 |
207 |
380 |
Not harsh enough |
498 |
630 |
1,128 |
|
Total |
805 |
972 |
N = 1,777 |
| Expected | E=(Column total*Row total)/Total | Male | Female | Total |
| Too harsh |
121.860 |
147.140 |
269 |
|
| About Right |
172.144 |
207.856 |
380 |
|
| Not too harsh |
510.996 |
617.004 |
1128 |
|
| Total |
805 |
972 |
1777 |
|
f o |
f e |
f o - f e | (f o - f e ) 2 | ||
| Male/Too harsh |
134 |
121.860 |
12.14 |
147.3796 |
1.21 |
| Male/About right |
173 |
172.144 |
0.856 |
0.7327 |
0.004 |
| Male/Not harsh enough |
498 |
510.996 |
-12.996 |
168.896 |
0.331 |
| Female/Too harsh |
135 |
147.140 |
-12.14 |
147.3796 |
1.002 |
| Female/About right |
207 |
207.856 |
-0.856 |
0.7327 |
0.004 |
| Female/Not harsh enough |
639 |
617.004 |
21.996 |
483.824 |
0.784 |
| 2 = 1.21+0.004+0.331+1.002+0.004+0.784=3.335 | |||||
Based on an alpha of 0.05, do you reject the null hypothesis?
From the chi-square distribution table, the probability level for Df of 2 and alpha 0.05 is 5.991. Therefore, accept the null hypothesis since 3.335 is less than 5.991.
