# QUESTION 1

STATISTICS PROJECT 6

QUESTION1

1. There are 2 groups being compared.

2. The sample size is 301.

3. The null hypothesis is to be rejected because the p-value (0.004) is less than 0.05

4. The results are statistically significant.

5. The Post-Hoc tests were used because the p-value is less than 0.05.it is run to know where the statistical difference arises.

QUESTION2

a)Nullhypothesis: there were no significant differences between regions intolerance of abortion for 2010 GSS middle-age adults.

Researchhypothesis: there were significant differences between regions intolerance of abortion for 2010 GSS middle-age adult.

 Descriptive Abortion Should Be Possible Index (asked about 6 situations) N Mean Std. Deviation Std. Error 95% Confidence Interval for Mean Minimum Maximum Lower Bound Upper Bound Northeast 153 4.47 2.007 .162 4.15 4.79 0 6 Midwest 238 3.62 2.044 .132 3.36 3.88 0 6 South 327 3.83 2.051 .113 3.61 4.06 0 6 West 167 4.49 1.866 .144 4.20 4.77 0 6 Total 885 4.01 2.037 .068 3.87 4.14 0 6
 ANOVA Abortion Should Be Possible Index (asked about 6 situations) Sum of Squares df Mean Square F Sig. Between Groups 116.809 3 38.936 9.660 .000 Within Groups 3551.119 881 4.031 Total 3667.928 884

Thesignificance value is less than 0.05.This indicates that there is asignificant difference between the group means. We reject the nullhypothesis, and so we proceed to carry out the Post-Hoc sTests inorder to know where the difference arises.

 Post-Hoc Tests Dependent Variable:Abortion Should Be Possible Index (asked about 6 situations) (I) Region of Current Residence (J) Region of Current Residence Mean Difference (I-J) Std. Error Sig. Tukey HSD Northeast Midwest .853* .208 .000 South .636* .197 .007 West -.014 .225 1.000 Midwest Northeast -.853* .208 .000 South -.217 .171 .582 West -.867* .203 .000 South Northeast -.636* .197 .007 Midwest .217 .171 .582 West -.650* .191 .004 West Northeast .014 .225 1.000 Midwest .867* .203 .000 South .650* .191 .004 Dunnett t (2-sided)b Northeast West -.014 .225 1.000 Midwest West -.867* .203 .000 South West -.650* .191 .002 *. The mean difference is significant at the 0.05 level. b. Dunnett t-tests treat one group as a control, and compare all other groups against it.

QUESTION3

1. paired sample t-test

2. chi-square

3. one-way ANOVA

4. independent sample t-test

5. paired sample t-test

6. one sample t-test

7. chi-square

8. independent sample t-test

9. paired sample t-test

10. chi-square

QUESTION4

Nullhypothesis: There is no significant relationship between region ofthe country and race of the 2010 GSS.

Researchhypothesis: There is a significant relationship between region ofthe country and race of the 2010 GSS.

 Case Processing Summary Cases Valid Missing Total N Percent N Percent N Percent Race of Respondent * REGION = 3 (FILTER) 475 100.0% 0 0.0% 475 100.0%
 Chi-Square Tests Value df Asymp. Sig. (2-sided) Pearson Chi-Square 87.648a 6 .000 Likelihood Ratio 83.609 6 .000 Linear-by-Linear Association 7.883 1 .005 N of Valid Cases 1258 a. 0 cells (0.0%) have expected count less than 5. The minimum expected count is 11.57.

Thevalue of chi-square is 87.648 and the degrees of freedom are 6. Thesignificance level is 0.000. The probability of a chi-square istherefore 0.000. Therefore we reject the null hypothesis withindependence. The result is statistically significant.

References

Anderson,D. R., Burnham, K. P., &amp Thompson, W. L. (2000). Null hypothesistesting: problems, prevalence, and an alternative.&nbspThejournal of wildlife management,912-923.

Gardner,M. J., &amp Altman, D. G. (1986). Confidence intervals rather than Pvalues: estimation rather than hypothesis testing.&nbspBMJ,&nbsp292(6522),746-750.

Davies,R. B. (1987). Hypothesis testing when a nuisance parameter is presentonly under the alternative.&nbspBiometrika,&nbsp74(1),33-43.