Research Design for One-Way ANOVA

Research question; what is the statistically significant variance in the mean income among the females and males? 

Null hypothesis; H 0 : a statistically significant variance does not exist in the mean income among the females and males. 

Research design; experimental designs are the research design, which may align with this test. The kind of innovative composition suitable for the question exists as a within-subject design since every subject is tested in every condition. 

Variables; A one-way ANOVA only has one independent variable ( Weinberg, & Abramowitz, 2002) . The variables that this case uses are the factor and dependent variables. The dependent is taken as salary as the factor variable is taken as gender. In a One-way ANOVA, one ought to have categorical independent variables (Hamilton, 2009), which in this instance is gender. Additionally, it should also be the factor variable. Therefore, the dependent variable should be continuous as one has income in this situation. The variables were selected since they meet the requirements above. 

The Dependent variable; it is the respondent’s Income. One can measure the variable by the sum of dollars, which a Respondents earn. 

The independent variable. It is the Respondent’s gender. One cannot measure the variable since it is categorical. 

Strength and significance of effect; the Significance is in this t-test.  Because the P-value is 0.00, the power of the force is reliable. Simply put, it has a perfect outcome. 

The answer to the research question and the Lay audience. 

The hypothesis question was that what is the statistically significant variance in the mean income among the females and males? From the data, the output shows this as an incorrect hypothesis. The outcome indicates that women and men earn differently. The men earn significantly higher compared to the women. 

References 

Hamilton, L. C. (2009).  Statistics with Stata: Updated for version 10 . Belmont, Calif: Brooks/Cole. 

Weinberg, S. L., & Abramowitz, S. K. (2002).  Data analysis for the behavioral sciences using SPSS . Cambridge: Cambridge University Press.