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(B) Age group and Marital Status

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Table of content

Title Page………………………………………………………………………………………….1

Table of content………………………………………………………………………………….2

Interpretation Questions…………………………………………………………………………3

7.1: Run the crosstabs and interpret the results of the chi-square and phi as discusses in chapter 7 and in interpretation of output 7.1………………………………………………….3

(A) Academic Track and Marital Status……………………………………………………….3

(B) Age group and Marital Status……………………………………………………….…….3

7.2: Select two other appropriate variables; run and interpret the output as we did in output 7.1

7.3 Is there an association between having children or not and watching TV sitcoms?References

7.1: run the crosstabs and interpret the results of the chi-square and phi as discusses in chapter 7 and in interpretation of output 7.1 for: (a) academic track and marital status and the (b) age group and the marital status.

(A) Academic Track and Marital Status

The results of the cross tabulation the chi-square test can help determine the test to help the tests determine the relationship of the nominal variables. The valid processing summary is 49 which were out of 50 that is missing data. The data a lot of information was give about academic track and the marital status gathered. When looking at the crosstab for when reviewing each tab have met the criteria. Best understand these results is find the proportion between the results of each cells between the academic track and the marital status. Thus, the expected results from the figures. Chi-square tests to show why the test we make making the decision on compering the results following the Academic Track and Marital Status getting the results are even more extreme when interpret the results of the chi-square test. When reviewing the results of the age group and in the figures the expected to be less than 5 for the conditions of the chi square test and the information that was giving. There is significance difference between the two variables. Marital status has more importance on whether the participate going to have children or not.

(B) Age group and Marital Status

Crosstabs for age group and marital status 49 was valid and one of the cases was missing 1 for participant missing data. Figure more data can be gathered following the information of age group and the marital status. Out of 22
participants 12 less than 22 were single 7 between the age group of 22-29 were single 3 30 or more were single in the age group crosstabulation. When looking at the actual count the expected of the comparison to the actual seen fewer participants meeting the age group and the marital status expectations (Mediratta & Mathur, 2023). Formulate the above-mentioned chi-square test and rank-based correlation estimators through a WCR-based U-statistic framework such that the established statistical properties for standard 
U-statistics of independent and identically distributed samples can be applied. Person chi-square of 18.023 have to determine the significance of the two of the age group and the marital status if the people are married or not.

7.2: Select two other appropriate variables; run and interpret the output as we did in output 7.1

Appropriate variables run and interpret between watching TV shows and watching TV sports. 50 participates provided data no participates was missing data according to the case processing summary the percent was 0.0%. In addition to the IBM SPSS statistics that a lot of data has been giving according to sources of the crosstabulation. Out of 20 participates 14 replied with yes of watching sports 6 replied with no of watching sports according to the data provide in the crosstabulation. When reviewing the data of the IBM the data shows that fewer participates than expected when running the data between TV shows and TV sports. Th valid condition of the chi-square test and the phi the value can be information can be interrupted by the symmetric measures. Chi-square measured to 5.333 and the phi-

7.3 Is there an association between having children or not and watching TV sitcoms?

When review the data about having children and not watching tv the sitcoms the crosstabulation show the subject of children watching television shows of 24 is 16 are watching tv sitcoms and no are not watching television sitcom shows. Looking at the figures can show the data between children and watching TV sitcoms with the chi-square test results. 50 people have participating and no missing data have with the case processing summary. Pearson chi-square is .855 and the approximate significance shows a data of .355 and a value of -.131 between having children or not and watching TV sitcoms.

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BUSI 820 QUANTITATIVE RESEARCH METHODS: ASSIGNMENT 5

References

Morgan, G. A., Barrett, K. C., Leech, N. L., & Gloeckner, G. W. (2020). IBM SPSS for

introductory statistics: Use and interpretation, sixth edition (6th ed.). Routledge


References

BUSI 820 QUANTITATIVE RESEARCH METHODS: ASSIGNMENT 5

References

Morgan, G. A., Barrett, K. C., Leech, N. L., & Gloeckner, G. W. (2020). IBM SPSS for

introductory statistics: Use and interpretation, sixth edition (6th ed.). Routledge

Mediratta, S., & Mathur, P. (2023). Understanding of nutrition information on food labels among higher income adults in India. 
Health Education Journal.
82(4), 461–472.

BUSI 820 QUANTITATIVE RESEARCH METHODS: ASSIGNMENT 5

References

Morgan, G. A., Barrett, K. C., Leech, N. L., & Gloeckner, G. W. (2020). IBM SPSS for

introductory statistics: Use and interpretation, sixth edition (6th ed.). Routledg

BUSI 820 QUANTITATIVE RESEARCH METHODS: ASSIGNMENT 5

References

Morgan, G. A., Barrett, K. C., Leech, N. L., & Gloeckner, G. W. (2020). IBM SPSS for

introductory statistics: Use and interpretation, sixth edition (6th ed.). Routledg

Morgan, G. A., Barrett, K. C., Leech, N. L., & Gloeckner, G. W. (2020). IBM SPSS for

introductory statistics: Use and interpretation, sixth edition (6th ed.). Routledge

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