T-Test and Chi-Test Assignment Example | Topics and Well Written Essays - 500 words

T-Test and Chi-Test - Assignment Example It is scientifically proven by Ridley (1999) the fact that men and women are different from each other. And they also differ in their motivational styles. Still, employment agencies will have to disregard the gender when it comes to a job working, so the aim of the employers are to motivate them using different tools that are available for them to use their abilities. The research that was carried out by Wiedner (1998) regarding personality type, etc. presented as determinants of job satisfaction has scrutinized the other factors such as age, educational level, sex, and the part-time and full-time status of the worker. And the one-way analysis of variance has been computed to determine if there are significant differences among the pay satisfaction levels. As the null hypothesis believed that there is no significant difference among the three shift categories. While on the other hand, the alternative hypothesis states that there is significance that exists on at least one of pair. Th is is just the same with the study in Unit 1, but the variance indicates that there is an insignificant difference that the level of education did not have the critical impact on their perception of equity on their perception of equity on pay. Here our finding is that there is a significant relationship in the differences between men and women regarding job satisfaction. As we observe from the first regression. And on the table we made, we have come up with a perfect correlation indicating that we have a positive result. There came the difference between the two regressions. When x and y switch, the result was changed. As the formula was: y = bx+a/y to get they we cross multiply the equation this way y = bx + a.   1 Y Their both sums came to become different and they both contrasts with each other since their composition was changed. They now represent another equation. The conclusion somewhat came to be undecided since it's different to explain both regressions with different dat a in it.