Introduction
It is conventional that at some point in life one has to look for a partner and get married, the marital status is affected by many factors. Some of the factors may include age, culture, and educational level and so on. The analysis in this section will tend to explore if the marital status of an individual has some relationship with the gender of the said individual. It will explore this relationship by the use of the contingency table to show the distribution after which a chi-square test will be performed to prove whether or not a relationship exists between marital status and gender.
Relationship
Hypothesis
Null hypothesis: there is no relationship between the gender and the marital status of the respondents (Smith et al. 2009). This can also be stated as there is independence between gender and the marital status. This is to say that the chi-square is equal to 0
Alternative hypothesis: there is a relationship between the gender and the marital status of the respondents. This can also be stated as there is dependence between gender and the marital status. This is to say that the chi-square is not equal to 0
The next step is to compute the chi-square value and find whether it is significant or not. The value can be generated by any statistical program.
Data
The data given below is for the marital status of both male and female. The main aim of the analysis is to explore whether there is an association between the gender and the marital status. The gender is categorized as male and female while the marital status is categorized as never married, married, living with a significant other, separated, widowed and divorced. The table below is a contingency table to show the distribution of gender among the categories.
Contingency table
The table below shows the row percentage
The table below shows the column percentage
The column percentage gives the percentage distribution of the marital status in relation to the gender of male and female. From the table, it can be seen that the females are the majority in all the categories with a higher difference in the category of the divorced and a smaller difference in the category of separated.
The program also produces the significance of this value. This chi-square value is said to be significant if the significance value is less than 0.05, otherwise it is significant.
The output is as shown below
(2-1) * (6-1)
This gives 5. The 5 is the degree of freedom.
Conclusion
Failure to reject the null hypothesis from the analysis leads to the conclusion that there is no relationship between the gender and the marital status. The categories of male and female have no association or dependence with the marital statuses of married, married, living with a significant other, separated, widowed and divorced. One can therefore not say that the marital status of an individual has a relationship with the gender. There is no enough evidence to prove whether there is existence of a significant relationship.
References
Albright, S. C., Winston, W. L., & Zappe, C. J. (2011). Data analysis and decision making. Mason, Ohio: South-Western/Cengage Learning.
Smith, L. F., Gratz, Z. S., & Bousquet, S. (2009). The art and practice of statistics. Belmont, CA: Wadsworth Cengage Learning.
