Part A SPSS output

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%

Chi-Square Tests

Value

df

Asymp. Sig. (2-sided)

Pearson Chi-Square

27.882a

9

.001

Likelihood Ratio

27.588

9

.001

Linear-by-Linear 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%

Chi-Square Tests

Value

df

Asymp. Sig. (2-sided)

Pearson Chi-Square

32.738a

12

.001

Likelihood Ratio

33.210

12

.001

Linear-by-Linear 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%

Chi-Square Tests

Value

df

Asymp. Sig. (2-sided)

Pearson Chi-Square

27.358a

2

.000

Likelihood Ratio

28.525

2

.000

Linear-by-Linear 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%

Chi-Square Tests

Value

df

Asymp. Sig. (2-sided)

Exact Sig. (2-sided)

Exact Sig. (1-sided)

Pearson Chi-Square

2.154a

1

.142

Continuity Correctionb

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 Chi-square 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%

Chi-Square Tests

Value

df

Asymp. Sig. (2-sided)

Pearson Chi-Square

.295a

2

.863

Likelihood Ratio

.295

2

.863

Linear-by-Linear 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 chi-square test shows that the value of chi-squareobtained 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%

Chi-Square Tests

Value

df

Asymp. Sig. (2-sided)

Exact Sig. (2-sided)

Exact Sig. (1-sided)

Pearson Chi-Square

3.086a

1

.079

Continuity Correctionb

2.879

1

.090

Likelihood Ratio

3.076

1

.079

Fisher`s Exact Test

.082

.045

Linear-by-Linear 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%

Chi-Square Tests

Value

df

Asymp. Sig. (2-sided)

Exact Sig. (2-sided)

Exact Sig. (1-sided)

Pearson Chi-Square

14.406a

1

.000

Continuity Correctionb

14.024

1

.000

Likelihood Ratio

14.267

1

.000

Fisher`s Exact Test

.000

.000

Linear-by-Linear 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.