Research question
Is there a statistically significant difference in the mean income between males and females?
Null hypothesis
H0: There is no statistically significant difference in the mean income between males and females.
Research design
The research design that would align with this test is experimental designs. The type of experimental design appropriate for this question is a within-subject design. This is because; each subject was tested in each condition.
Variables
The variables used in this case are the dependent variable and the factor variables also called the independent variable. The dependent variable was taken as income while the factor variable was taken as gender. In a One-way ANOVA, we must have independent categorical variables in this case gender which must also be the factor variable and the dependent variable must be continuous as we have income in this case. Thus, these variables were chosen since they met these requirements.
Dependent variable
The dependent variable is the variable to be explained, in this assignment this is the Income of the Respondent.
This variable is measured by the amount in dollars that a Respondent earns.
Independent variable
The independent variable is the cause of the dependent variable; in this case it is the Sex of the Respondent.
This variable is not measurable since it is categorical.
Significance and strength of effect
Significance was found in this t-test. Since the P-value was found to be 0.00, the strength of the effect is very strong. In other words, it is a perfect effect.
Lay audience, and answer to the research question.
My hypothesis question was that, there is no statistically significant difference in the mean income between males and females. The output from the data proved this to be an incorrect hypothesis. The results indicated that men and women earn differently. Men earn significantly higher than women.
Below is the SPSS output for the Study.
| N | Mean | Std. Deviation | Std. Error | 95% Confidence Interval for Mean | Minimum | Maximum | ||
| Lower Bound | Upper Bound | |||||||
| MALE | 750 | 10.70 | 2.745 | .100 | 10.50 | 10.90 | 1 | 12 |
|---|---|---|---|---|---|---|---|---|
| FEMALE | 773 | 10.08 | 3.039 | .109 | 9.86 | 10.29 | 1 | 12 |
| Total | 1523 | 10.38 | 2.914 | .075 | 10.24 | 10.53 | 1 | 12 |
| Sum of Squares | df | Mean Square | F | Sig. | |
| Between Groups | 148.066 | 1 | 148.066 | 17.630 | .000 |
|---|---|---|---|---|---|
| Within Groups | 12773.997 | 1521 | 8.398 | ||
| Total | 12922.063 | 1522 |
The Procedure for Obtaining the Above output was as follows:
Press OK to produce output
- Click Analyze > Compare Means > One-Way ANOVA… on the main menu:
- Click on variable Respondents Income and use the arrow button to move it to the Dependent list box.
- Click on variable Respondents Sex and use the arrow button to move it to the Factor box.
- Click on the Options button. You will be presented with the One-Way ANOVA: Options box. Mark on the Descriptive option and press Continue.
- Click the Post-Hoc button and check on the Tukey’s-b Option and Press Continue.
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