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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(Klingenberg, 2016). 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 a number of 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 (Kass, Eden, & Brown, 2014).

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 have different income.  Men earn significantly higher than women (Laureate Education, 2016h).

Below is the SPSS output for the Study.

 

Descriptives

 

RESPONDENTS INCOME

 

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

 

 

 

ANOVA

RESPONDENTS INCOME

 

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

 

 

 

 

 

 

 

 

 

 

 

References

Kass, R. E., Eden, U. T., & Brown, E. N. (2014). Analysis of variance. In Analysis of Neural Data (pp. 361-389). Springer New York.

Klingenberg, B. (2016). ANOVA: Analysis of variance. Retrieved from https://istats.shinyapps.io/ANOVA/

Laureate Education (Producer). (2016h). One-way ANOVA demonstration [Video file]. Baltimore, MD: Author.

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