2. Partial tables Suppose a researcher wishes to analyze the relationship between an individual's amount of yearly vacation time and that individual's stress level. For this study, the researcher has decided to focus on stress levels of single women. From a sample of 296 single women, the researcher collects information from all the subjects about their stress (Y) levels and how much time they spend on vacation every year. Vacation time (X) is reported as low if an individual spends 7 days or fewer per year on vacation and high if the individual spends more than 7 days per year on vacation. After collecting the results from the study, the researcher constructs the following bivariate table for X and Y. Find the column percentages and compute the gamma. Complete the table by selecting the correct values from the dropdown menus provided. Stress Level (Y) Totals Low Vacation Time (X) Low High 34(%) 108 %) 78( %) 76 %) 112 (100.0%) 184 (100.0%) 142 High 154 Totals 296 Gamma = The data in the table show association between these variables. Suppose you decide to investigate the possible effect that an individual's income level might have on the relationship between vacation time and stress level. You collect data on income level and classify the results into one of two categories: whether an individual has a yearly income below $40,000 (Low) or $40,000 or higher (High). The partial tables showing the bivariate relationships for individuals in each category follow. Find the column percentages and compute the gammas for each. Complete the tables by selecting the correct values from the dropdown menus provided. A. Low Income Stress Level (Y) Totals Low Vacation Time (X) Low High 25 (%) %) 100 %) 41(%) 35 (100.0%) 144 (100.0%) 103 128 High 51 Totals 179 Gamma = B. High Income Stress Level (Y) Totals Low Vacation Time (X) Low High 9 %) 50 %) 68 %) 35(%) 77 (100.0%) 40 (100.0%) 14 High 103 Totals 117 Gamma = Compared with the bivariate table, the partial tables show relationship between vacation time and stress level. This is evidence of relationship between the variables and implies you should the variable 2 (income level) in further analysis. 2. Partial tables Suppose a researcher wishes to analyze the relationship between an individual's amount of yearly vacation time and that individual's stress level. For this study, the researcher has decided to focus on stress levels of single women. From a sample of 296 single women, the researcher collects information from all the subjects about their stress (Y) levels and how much time they spend on vacation every year. Vacation time (X) is reported as low if an individual spends 7 days or fewer per year on vacation and high if the individual spends more than 7 days per year on vacation. After collecting the results from the study, the researcher constructs the following bivariate table for X and Y. Find the column percentages and compute the gamma. Complete the table by selecting the correct values from the dropdown menus provided. Stress Level (Y) Totals Low Vacation Time (X) Low High 34(%) 108 %) 78( %) 76 %) 112 (100.0%) 184 (100.0%) 142 High 154 Totals 296 Gamma = The data in the table show association between these variables. Suppose you decide to investigate the possible effect that an individual's income level might have on the relationship between vacation time and stress level. You collect data on income level and classify the results into one of two categories: whether an individual has a yearly income below $40,000 (Low) or $40,000 or higher (High). The partial tables showing the bivariate relationships for individuals in each category follow. Find the column percentages and compute the gammas for each. Complete the tables by selecting the correct values from the dropdown menus provided. A. Low Income Stress Level (Y) Totals Low Vacation Time (X) Low High 25 (%) %) 100 %) 41(%) 35 (100.0%) 144 (100.0%) 103 128 High 51 Totals 179 Gamma = B. High Income Stress Level (Y) Totals Low Vacation Time (X) Low High 9 %) 50 %) 68 %) 35(%) 77 (100.0%) 40 (100.0%) 14 High 103 Totals 117 Gamma = Compared with the bivariate table, the partial tables show relationship between vacation time and stress level. This is evidence of relationship between the variables and implies you should the variable 2 (income level) in further analysis
