Now that you have completed the first six assignments, it is time to complete your research project for the course. Include the following sections in your submission. Title Page Table of Contents Ex
DATA ANALYSIS: HYPOTHESIS TESTING 0
DATA ANALYSIS: HYPOTHESIS TESTING
Jermaine Griffin
Independent Samples t Test: Hypothesis Testing
The main null hypothesis (Ho) being analyzed is that there is no statistical difference between individual groups that have undergone training and those that have not undergone training. The independent t-test indicates a statistically significant performance results between group A and group B. This test results a p value of less than 0.05 which is 1.94E-15. It is worth noting that the p value is usually used to the measure the level of statistical significance between various variables (Nahm, 2017 p.241). This provision can be attributed to the fact that the performance of the groups is impacted by the level of training thus opposing the H0 hypothesis which states that there is no statistical difference between the two groups despite the training.
Ha: There is a statistically significant difference in the scores between Group A training scores and Group B testing scores.
| t-Test: Two-Sample Assuming Unequal Variances | |||
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| Group A Prior Training Scores | Group B Revised Training Scores | |
| Mean | 69.79032258 | 84.77419355 | |
| Variance | 122.004495 | 26.96456901 | |
| Observations | 62 | 62 | |
| Hypothesized Mean Difference | |||
| df | 87 | ||
| t Stat | -9.666557191 | ||
| P(T<=t) one-tail | 9.69914E-16 | ||
| t Critical one-tail | 1.662557349 | ||
| P(T<=t) two-tail | 1.93983E-15 | ||
| t Critical two-tail | 1.987608282 |
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Dependent Samples (Paired Samples) t Test: Hypothesis Testing
Ho: There is no statistically significant difference between the impact on employee before and after the exposure.
| t-Test: Paired Two Sample for Means | |||
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| Pre-Exposure μg/dL | Post-Exposure μg/dL | |
| Mean | 32.85714286 | 33.28571429 | |
| Variance | 150.4583333 | 155.5 | |
| Observations | 49 | 49 | |
| Pearson Correlation | 0.992236043 | ||
| Hypothesized Mean Difference | |||
| df | 48 | ||
| t Stat | -1.929802563 | ||
| P(T<=t) one-tail | 0.029776357 | ||
| t Critical one-tail | 1.677224196 | ||
| P(T<=t) two-tail | 0.059552714 | ||
| t Critical two-tail | 2.010634758 |
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According to the paired t-test, there seems to be significant effect before and after exposure. This provision is supported by statistical findings p (T<=t) = 0.0297764 which indicates a very significant difference between the two test results.
Ho: There is no statistically significant difference between the impact on employee before and after the exposure. This hypothesis is rejected according the statistical analysis.
Ha: There is no statistically significant difference between the impact on employee before and after the exposure which is indicated by the low p value.
ANOVA: Hypothesis Testing
Ho: There is no statistically significant difference between the impact on employee before and after the exposure.
| Anova: Single Factor | ||||||
| SUMMARY | ||||||
| Groups | Count | Sum | Average | Variance | ||
| A = Air | 20 | 178 | 8.9 | 9.357895 | ||
| B = Soil | 20 | 182 | 9.1 | 3.042105 | ||
| C = Water | 20 | 140 | 6.631579 | |||
| D = Training | 20 | 108 | 5.4 | 1.410526 | ||
| ANOVA | ||||||
| Source of Variation | SS | df | MS | F | P-value | F crit |
| Between Groups | 182.8 | 60.93333 | 11.9231 | 1.76E-06 | 2.724944 | |
| Within Groups | 388.4 | 76 | 5.110526 | |||
| Total | 571.2 | 79 |
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According to the one-way ANOVA analysis, there is significant difference between the various types of project returns. There significance can be observed from the variance an average mean outputs as well as from the various coefficients used in the ANOVA analysis table.
Ho: There is no statistically significant difference between the impact on employee before and after the exposure. The analysis indicates a p-value of 1.75887702754493E-06 which is below the p-value of 0.5 that which is against the null hypothesis that indicates that there are no significant differences between the return on investments of the different groups of investments.
Ha: There is statistically significant difference between the impact on employee before and after the exposure which is an acceptable hypothesis based on the ANOVA analysis results.
References
Nahm, F. S. (2017). What the P values really tell us. The Korean Journal of Pain, 30(4), 241. https://doi.org/10.3344/kjp.2017.30.4.241
