Previous Assignment- The last one you completed.

0

Factorial Analysis of Variance

Student Name

University

Introduction

This paper is based on Factorial Analysis of Variance, also known as Factorial ANOVA. The use of Factorial ANOVA is to compare various means across independent variables. Unlike a one-way ANOVA, Factorial ANOVA has at least two independent variables. When two independent variables are used as in this case, they are split into four groups. The independent variables used in this case are Rs occupational prestige score (2010) and Rs occupational prestige score using threshold method (2010) with Father’s Occupation Prestige Score as the dependent variable.

Research Question

RQ: What is the relationship between Rs occupational prestige score (2010) and Rs occupational prestige score using threshold method (2010) when determining the occupational satisfaction of employees.

Hypotheses

Null Hypothesis (H0): There is no statistically significant relationship between Rs occupational prestige score (2010) and Rs occupational prestige score using threshold method (2010) when determining the occupational satisfaction of employees.

Alternative Hypothesis (HA): The is statistically significant relationship between Rs occupational prestige score (2010) and Rs occupational prestige score using threshold method (2010) when determining the occupational satisfaction of employees.

Variables

Dependent Variables (IV)

• Father’s occupation prestige score - The score ranges between 1 and 100.

Independent Variables (DV)

• Rs occupational prestige score (2010)

• Rs occupational prestige score using threshold method (2010)

Results

As required, a factorial analysis of variance of contacted to establish the level of relationship between the independent variable and their effect on the dependent variable. The results of the SPSS output are depicted the table below:

Table 1: Tests of Between-Subjects Effects

Source: SPSS Output

The key aspects of the results considered include the p-value and significant level. From the results, the p-value for the variable Rs occupational prestige score (2010) is 0. In this regard, we conclude that the variable is significant (Statistics Solutions, 2017). The p-value for Rs occupational prestige score using threshold method (2010) is not significant because it is 0.73, which is greater than p = 0.05, which is less than the p-value. This means that prestige score does not change among individuals (Statistics Solutions, 2017). The p-value for the intersection is 0.17, which is also not significant. Because the intersection is not significant, we can conclude that the effect of Rs occupational prestige score (2010) on Rs occupational prestige score using the threshold method (2010) among Father’s occupation prestige scores is the same. As such, we accept the null hypothesis that There is no statistically significant relationship between Rs occupational prestige score (2010) and Rs occupational prestige score using threshold method (2010) when determining the occupational satisfaction of employees. The alternative hypothesis is rejected.

References

Statistics Solutions. (2017). Conduct and Interpret a Factorial ANOVA. Retrieved June 28, 2017, from Statisticssolutions.com: http://www.statisticssolutions.com/conduct-interpret-factorial-anova/

Appendix

Table 2: Between-Subjects Factors

Table 3: Tests of Between-Subjects Effects