Your Data Interpretation Practicum
To investigate the research question, the study formulated the following hypothesis:
H0: The rate of occurrence of risks is the same for the employees under female and male supervisors in the three manufacturing locations.
H1: The rate of risks occurrence is different for the employees under female and male supervisors in the three manufacturing locations.
From the available data, the rate of risk occurrence can be tested through the analysis 3 variables which are; injury rate, safety climate and risk. An independent samples t-test of each variable will be conducted against gender which is the grouping variable at a 95% confidence interval.
a). The first hypothesis to be tested is;
H0: The injury rate is the same for the employees under female and male supervisors in the three manufacturing locations.
Vs
H1: The injury rate is different for the employees under female and male supervisors in the three manufacturing locations
| Group Statistics | |||||
| SupervisorGender | N | Mean | Std. Deviation | Std. Error Mean | |
| InjuryRate | 1 | 24 | 1.353291E1 | 12.9881295 | 2.6511908 |
| 2 | 27 | 1.663595E1 | 20.8160156 | 4.0060441 |
Table 1
| Injury rate | Levene’s Test for Equality of Variances | ||||||||
| F | Sig | t | df | Sig.(2-tailed) | Mean Difference | Std. Error Difference | 95% Confidence Interval of the Difference | ||
| Equal var. assumed Equal var. not assumed | 1.662 | .203 | -.609 -.646 | 49 44.182 | .532 .522 | -3.10304 -3.10304 | 4.93226 4.80387 | Lower | Upper |
| -13.0148 -12.7834 | 6.8087189 6.5774012 |
Table 2.
The above table shows the output obtained after carrying out an independent samples t test.
Decision Rule
Reject H0 if . From table 2 above, p value = 0.532 which is greater than 0.05 hence we accept the null hypothesis.
Conclusion
We can conclude that the injury rate is the same for the employees under female and male supervisors in the three manufacturing locations at 95% level of precision. The results indicated that the injury rate for employees under male supervisors (M = 1.353, SD =12.98) was not significantly different from injury rate for employees under female supervisors (M = 1.663, SD = 20.816), t(49) = -.609, p> .05 i.e. 0.532. The injury rate is the same for employees under male and female supervisors in the 3 locations at 95% level of precision where 95% confidence interval for the mean difference between the male and female cases was -13.0148 to 6.8087189
b). The second hypothesis to be tested is;
H0: The safety climate is the same for the employees under female and male supervisors in the three manufacturing locations.
Vs
H1: The safety climate is different for the employees under female and male supervisors in the three manufacturing locations
| Group Statistics | |||||
| SupervisorGender | N | Mean | Std. Deviation | Std. Error Mean | |
| SafetyClimate | 1 | 24 | 4.391250E0 | .8626466 | .1760870 |
| 2 | 27 | 4.968889E0 | 1.1129183 | .2141812 |
Table 3.
| Safety climate | Levene’s Test for Equality of Variances | ||||||||
| F | Sig | t | df | Sig.(2-tailed) | Mean Difference | Std. Error Difference | 95% Confidence Interval of the Difference | ||
| Equal var. assumed Equal var. not assumed | 1.489 | .228 | -2.052 -2.083 | 49 48.15 | .045 .043 | -.577638 -.577638 | .281453 .277272 | Lower | Upper |
| -1.14324 -1.13508 | -.012037 -.020191 |
Table 4.
The above table shows the output obtained after carrying out an independent samples t test.
Decision Rule
Reject H0 if . From table 4 above, p value = 0.045 which is less than 0.05 hence we reject the null hypothesis.
Conclusion
We can conclude that the safety climate is the different for the employees under female and male supervisors in the three manufacturing locations at 95% level of precision. The results indicated that the safety climate for employees under male supervisors (M = 4.391, SD =0.8626) was significantly different from safety climate for employees under female supervisors (M = 4.968, SD = 1.112), t(49) = -2.052, p< .05 i.e. 0.045. The safety climate is the different for employees under male and female supervisors in the 3 locations at 95% level of precision where 95% confidence interval for the mean difference between the male and female cases was -1.14324 to – 0.012037
c). The third hypothesis to be tested is;
H0: The risk is the same for the employees under female and male supervisors in the three manufacturing locations.
Vs
H1: The risk is different for the employees under female and male supervisors in the three manufacturing locations
| Group Statistics | |||||
| SupervisorGender | N | Mean | Std. Deviation | Std. Error Mean | |
| Risk | 1 | 24 | 4.79 | 2.000 | .408 |
| 2 | 27 | 4.41 | 2.043 | .393 |
Table 5.
| Risk | Levene’s Test for Equality of Variances | ||||||||
| F | Sig | t | df | Sig.(2-tailed) | Mean Difference | Std. Error Difference | 95% Confidence Interval of the Difference | ||
| Equal var. assumed Equal var. not assumed | .052 | .820 | .677 .678 | 49 48.52 | .501 .501 | .384 .384 | .567 .567 | Lower | Upper |
| -.756 -.755 | 1.525 1.523 |
Table 6.
The above table shows the output obtained after carrying out an independent samples t test.
Decision Rule
Reject H0 if . From table 6 above, p value = .501 which is greater than 0.05 hence we accept the null hypothesis.
Conclusion
We can conclude that the risk is the same for the employees under female and male supervisors in the three manufacturing locations at 95% level of precision. The results indicated that the risk for employees under male supervisors (M = 4.79, SD =2.0) was not significantly different from risk for employees under female supervisors (M = 4.41, SD = 2.043), t(49) = .677, p> .05 i.e. 0.501. The risk is the same for employees under male and female supervisors in the 3 locations at 95% level of precision where 95% confidence interval for the mean difference between the male and female cases was -.756 to 1.525.
From the 3 tests, we conclude that the injury rate and risk is significantly the same for employees working under both male and female supervisors in the 3 working locations though the safety climate is significantly different.
BIBLIOGRAPHY.
Cooper, D. R., & Schindler, P. S. (2011). Business Research Methods (11th ed.). New York: McGraw-Hill/Irwin.
Creswell, J. W. (2003). Qualitative, quantitative, and mixed methods approaches(2nd ed.). Thousand Oaks, CA: Sage.
Ghauri, et al. (2005). Research Methods in Business Studies: a Practical Guide.
Kumar, R. (2009). Research Methodology: A step-by-step Guide for Beginners. Greater Kalash: Sage Publications.
