Statistical Analysis 1: ANOVA
Statistical Analysis 2: Regression
The regression model is satisfaction = 2.989 + 0.75Invest – 0.47alter + 0.509 commit.
The first term is the intercept term; that is when x=0, the value of satisfaction is 2.989. Holding other factors constant, a unit change in investment, there is a 75% increase in satisfaction. Holding other factors constant, a unit increase in alternatives leads to a 47% decrease in satisfaction. Lastly, holding other factors constant, a unit increase in commitment leads to a 50.9% increase in satisfaction. The coefficient of investment, alternatives, and commitment fall within the 95% confidence interval.
Statistical Analysis 3: Chi-Square Test of Independence
The number of people sampled in this survey was 336. Of this, 143 were males while 193 were females. The number of individuals dating causally is 45. Of this, 26 were males while 19 were females. The number of respondents who were seriously dating was 271. Of this, 105 were males while 166 were females. The number of respondents engaged or married was 20. Of this, 12 were males while 8 were females. It is noted that in each category females were more than males expect in the category of casual dating. The chi-square test in this research was conducted to examine the relationship between gender and status variable. The null hypothesis is that there is no rapport between gender and status. The alternative hypothesis is that there is no association between gender and status. From the chi-square test, the statistics is 8.364 while the significance value is 0.015. Since the significance value is less than 0.05 we fail to reject the null hypothesis and conclude that there is evidence of the relationship between gender and status.