Assignment on Spss
Assignment on SPSS
1. Correlations
Result of one-tailed test:
[pic]
Result of two-tailed test:
[pic]
Conclusion:
Based on the above tables, there is no difference on the correlations between four variables in using one-tailed test and two-tailed test.
2. Regression
Model summary:
[pic]
Coefficients:
[pic]
Scatterplot and regression line:
[pic]
Conclusion:
From the first table, as the value of R square is 0.09 (i.e. R = 0.3), it means that the overall quality has positive linear relationship with expected grade (as the above scatterplot and regression line you can see), and the equation of regression is: Overall quality = 1.718 + 0.526 x Expected grade.
3. One-sample t test
Result of one-sample test:
[pic]
*We set H0: μ = 20; HA: μ ≠ 20
Conclusion:
From the above table, as the p-value is smaller than 0.05 (significant level) and the test value (20) is not within the confidence interval (23.60 – 28.82), we reject H0, i.e. we have insufficient evidence to conclude that 20 is the expected value of data.
4. Mann-Whitney Test
Result of test statistics:
[pic]
H0: No birth weight difference between prenatal care in the first trimester and third trimester
HA: Having birth weight difference between prenatal care in the first trimester and third trimester
Conclusion:
From the above table, as the p-value (0.033) is smaller than 0.05, we do not reject H0, that means we have sufficient evidence to conclude that there is no birth weight difference between prenatal care in the first trimester and third trimester.
5. Wilcoxon’s Matched Pairs Signed Ranks Test
Result of test statistics:
[pic]
H0: Before = After; HA: Before ≠ After
Conclusion:
From the above table, as the p-value (0.002) is smaller than 0.05, we reject H0, so we have insufficient evidence to conclude that there is no difference between the subjects’ weight pre and post
1. Correlations
Result of one-tailed test:
[pic]
Result of two-tailed test:
[pic]
Conclusion:
Based on the above tables, there is no difference on the correlations between four variables in using one-tailed test and two-tailed test.
2. Regression
Model summary:
[pic]
Coefficients:
[pic]
Scatterplot and regression line:
[pic]
Conclusion:
From the first table, as the value of R square is 0.09 (i.e. R = 0.3), it means that the overall quality has positive linear relationship with expected grade (as the above scatterplot and regression line you can see), and the equation of regression is: Overall quality = 1.718 + 0.526 x Expected grade.
3. One-sample t test
Result of one-sample test:
[pic]
*We set H0: μ = 20; HA: μ ≠ 20
Conclusion:
From the above table, as the p-value is smaller than 0.05 (significant level) and the test value (20) is not within the confidence interval (23.60 – 28.82), we reject H0, i.e. we have insufficient evidence to conclude that 20 is the expected value of data.
4. Mann-Whitney Test
Result of test statistics:
[pic]
H0: No birth weight difference between prenatal care in the first trimester and third trimester
HA: Having birth weight difference between prenatal care in the first trimester and third trimester
Conclusion:
From the above table, as the p-value (0.033) is smaller than 0.05, we do not reject H0, that means we have sufficient evidence to conclude that there is no birth weight difference between prenatal care in the first trimester and third trimester.
5. Wilcoxon’s Matched Pairs Signed Ranks Test
Result of test statistics:
[pic]
H0: Before = After; HA: Before ≠ After
Conclusion:
From the above table, as the p-value (0.002) is smaller than 0.05, we reject H0, so we have insufficient evidence to conclude that there is no difference between the subjects’ weight pre and post