PartA SPSS output
11.1Do child care Practices vary by social class?
FAVOR SPANKING TO DISCIPLINE CHILD * SUBJECTIVE CLASS IDENTIFICATION Crosstabulation 

SUBJECTIVE CLASS IDENTIFICATION 
Total 

LOWER CLASS 
WORKING CLASS 
MIDDLE CLASS 
UPPER CLASS 

FAVOR SPANKING TO DISCIPLINE CHILD 
STRONGLY AGREE 
Count 
38 
167 
125 
10 
340 
% within SUBJECTIVE CLASS IDENTIFICATION 
33.0% 
28.6% 
22.4% 
23.8% 
26.2% 

AGREE 
Count 
49 
279 
261 
13 
602 

% within SUBJECTIVE CLASS IDENTIFICATION 
42.6% 
47.9% 
46.8% 
31.0% 
46.4% 

DISAGREE 
Count 
24 
116 
125 
14 
279 

% within SUBJECTIVE CLASS IDENTIFICATION 
20.9% 
19.9% 
22.4% 
33.3% 
21.5% 

STRONGLY DISAGREE 
Count 
4 
21 
47 
5 
77 

% within SUBJECTIVE CLASS IDENTIFICATION 
3.5% 
3.6% 
8.4% 
11.9% 
5.9% 

Total 
Count 
115 
583 
558 
42 
1298 

% within SUBJECTIVE CLASS IDENTIFICATION 
100.0% 
100.0% 
100.0% 
100.0% 
100.0% 
ChiSquare Tests 

Value 
df 
Asymp. Sig. (2sided) 

Pearson ChiSquare 
27.882^{a} 
9 
.001 
Likelihood Ratio 
27.588 
9 
.001 
LinearbyLinear Association 
18.303 
1 
.000 
N of Valid Cases 
1298 

a. 1 cells (6.3%) have expected count less than 5. The minimum expected count is 2.49. 
11.2.Do attitudes about immigration vary by social class?
NUMBER OF IMMIGRANTS TO AMERICA NOWADAYS SHOULD BE * SUBJECTIVE CLASS IDENTIFICATION Crosstabulation 

SUBJECTIVE CLASS IDENTIFICATION 
Total 

LOWER CLASS 
WORKING CLASS 
MIDDLE CLASS 
UPPER CLASS 

NUMBER OF IMMIGRANTS TO AMERICA NOWADAYS SHOULD BE 
INCREASED A LOT 
Count 
7 
20 
17 
2 
46 
% within SUBJECTIVE CLASS IDENTIFICATION 
6.4% 
3.4% 
3.1% 
5.0% 
3.6% 

INCREASED A LITTLE 
Count 
3 
40 
54 
6 
103 

% within SUBJECTIVE CLASS IDENTIFICATION 
2.8% 
6.9% 
9.7% 
15.0% 
8.0% 

REMAIN THE SAME AS IT IS 
Count 
39 
195 
202 
11 
447 

% within SUBJECTIVE CLASS IDENTIFICATION 
35.8% 
33.6% 
36.3% 
27.5% 
34.7% 

REDUCED A LITTLE 
Count 
21 
122 
151 
11 
305 

% within SUBJECTIVE CLASS IDENTIFICATION 
19.3% 
21.0% 
27.1% 
27.5% 
23.7% 

REDUCED A LOT 
Count 
39 
204 
133 
10 
386 

% within SUBJECTIVE CLASS IDENTIFICATION 
35.8% 
35.1% 
23.9% 
25.0% 
30.0% 

Total 
Count 
109 
581 
557 
40 
1287 

% within SUBJECTIVE CLASS IDENTIFICATION 
100.0% 
100.0% 
100.0% 
100.0% 
100.0% 
ChiSquare Tests 

Value 
df 
Asymp. Sig. (2sided) 

Pearson ChiSquare 
32.738^{a} 
12 
.001 
Likelihood Ratio 
33.210 
12 
.001 
LinearbyLinear Association 
7.312 
1 
.007 
N of Valid Cases 
1287 

a. 3 cells (15.0%) have expected count less than 5. The minimum expected count is 1.43. 
11.3Is Ignorance Bliss?
GENERAL HAPPINESS * rdeg Crosstabulation 

rdeg 
Total 

1.00 
2.00 

GENERAL HAPPINESS 
VERY HAPPY 
Count 
353 
246 
599 
% within rdeg 
27.3% 
34.2% 
29.7% 

PRETTY HAPPY 
Count 
701 
398 
1099 

% within rdeg 
54.1% 
55.4% 
54.6% 

NOT TOO HAPPY 
Count 
241 
75 
316 

% within rdeg 
18.6% 
10.4% 
15.7% 

Total 
Count 
1295 
719 
2014 

% within rdeg 
100.0% 
100.0% 
100.0% 
ChiSquare Tests 

Value 
df 
Asymp. Sig. (2sided) 

Pearson ChiSquare 
27.358^{a} 
2 
.000 
Likelihood Ratio 
28.525 
2 
.000 
LinearbyLinear Association 
24.355 
1 
.000 
N of Valid Cases 
2014 

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 112.81. 
PARTB11.5 (a)
status 

Salary 
Union 
Nonunion 
Totals 
High 
21 
29 
50 
Low 
14 
36 
50 
Totals 
35 
65 
100 
Inputtingthe above table and analyzing the same in the spss yield thefollowing spss outputs
Salary Level * Unionization of Public Employees Crosstabulation 

Unionization of Public Employees 
Total 

union 
Non union 

Salary Level 
High 
Count 
21 
29 
50 
% within Unionization of Public Employees 
60.0% 
44.6% 
50.0% 

Low 
Count 
14 
36 
50 

% within Unionization of Public Employees 
40.0% 
55.4% 
50.0% 

Total 
Count 
35 
65 
100 

% within Unionization of Public Employees 
100.0% 
100.0% 
100.0% 
ChiSquare Tests 

Value 
df 
Asymp. Sig. (2sided) 
Exact Sig. (2sided) 
Exact Sig. (1sided) 

Pearson ChiSquare 
2.154^{a} 
1 
.142 

Continuity Correction^{b} 
1.582 
1 
.208 

Likelihood Ratio 
2.165 
1 
.141 

Fisher`s Exact Test 
.208 
.104 

N of Valid Cases 
100 

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 17.50. b. Computed only for a 2×2 table In the Chisquare table above the reported sig is 0.208 which is much greater than 0.05 so we fail to reject the null hypothesis and conclude that the relationship between the two variables is not statistically significant hence there is no statisti relation between the unionization of public employees and the income. 11.5b). Analyzing the column percentage in the cross tabulation table, 60.0% of the union public employees get higher salary than the nonunion public employees. 
11.10a) is there a relationship between political ideology and socialclass standing?
Inputtingthe table given in the 11.10 in spss and analyzing the same in crosstab yield the following spss outputs
Political Ideology * Class standing Crosstabulation 

Class standing 
Total 

Under Class 
Upper Class 

Political Ideology 
Liberal 
Count 
43 
40 
83 
% within Class standing 
32.3% 
29.9% 
31.1% 

Moderate 
Count 
50 
50 
100 

% within Class standing 
37.6% 
37.3% 
37.5% 

Conservative 
Count 
40 
44 
84 

% within Class standing 
30.1% 
32.8% 
31.5% 

Total 
Count 
133 
134 
267 

% within Class standing 
100.0% 
100.0% 
100.0% 
ChiSquare Tests 

Value 
df 
Asymp. Sig. (2sided) 

Pearson ChiSquare 
.295^{a} 
2 
.863 
Likelihood Ratio 
.295 
2 
.863 
LinearbyLinear Association 
.292 
1 
.589 
N of Valid Cases 
267 

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 41.34. 
Theresults of the chisquare test shows that the value of chisquareobtained is 0.295 and the the degree of freedom is 2. The exactsignificance of chi square is 0.863 which is greater that thestandard indicator of standard result (alpa=0.05). We fail to rejectour null hypothesis and conclude that there is no statisticallyrelationship between the political ideology and the class standing.
11.10b) in the cross tabulation table above shows the pattern ofrelationship between the two variables. The column percent show thatthe upper classes are more likely to be conservatives with 32.8%
PARTC11.3
Crosstab 

rdeg 
Total 

1.00 
2.00 

SHOULD MARIJUANA BE MADE LEGAL 
LEGAL 
Count 
300 
196 
496 
% within rdeg 
37.9% 
43.0% 
39.8% 

NOT LEGAL 
Count 
491 
260 
751 

% within rdeg 
62.1% 
57.0% 
60.2% 

Total 
Count 
791 
456 
1247 

% within rdeg 
100.0% 
100.0% 
100.0% 
ChiSquare Tests 

Value 
df 
Asymp. Sig. (2sided) 
Exact Sig. (2sided) 
Exact Sig. (1sided) 

Pearson ChiSquare 
3.086^{a} 
1 
.079 

Continuity Correction^{b} 
2.879 
1 
.090 

Likelihood Ratio 
3.076 
1 
.079 

Fisher`s Exact Test 
.082 
.045 

LinearbyLinear Association 
3.084 
1 
.079 

N of Valid Cases 
1247 

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 181.38. b. Computed only for a 2×2 table 
Inthe chi square test the exact significance value is 0.082 which isgreater than our standard significance indicator of standard results(lpha=0.05) hence we conclude that there is no statisticallysignificance relationship between education and legalizing marijuana.
Crosstab 

rdeg 
Total 

1.00 
2.00 

FAVOR OR OPPOSE DEATH PENALTY FOR MURDER 
FAVOR 
Count 
850 
412 
1262 
% within rdeg 
69.4% 
60.9% 
66.4% 

OPPOSE 
Count 
374 
265 
639 

% within rdeg 
30.6% 
39.1% 
33.6% 

Total 
Count 
1224 
677 
1901 

% within rdeg 
100.0% 
100.0% 
100.0% 
ChiSquare Tests 

Value 
df 
Asymp. Sig. (2sided) 
Exact Sig. (2sided) 
Exact Sig. (1sided) 

Pearson ChiSquare 
14.406^{a} 
1 
.000 

Continuity Correction^{b} 
14.024 
1 
.000 

Likelihood Ratio 
14.267 
1 
.000 

Fisher`s Exact Test 
.000 
.000 

LinearbyLinear Association 
14.399 
1 
.000 

N of Valid Cases 
1901 

a. 0 cells (.0%) have expected count less than 5. The minimum expected count is 227.57. b. Computed only for a 2×2 table 
Inthe chi square test the exact significance value is 0.000 which isless than our standard significance indicator of standard results(alpha=0.05) hence we conclude that there is statisticallyrelationship between education and death penalty for murder.