Its due before the start your in-class final examthis assignment questions

If you decide to complete it, it’s due before the start of your in-class final exam
This assignment is 5 questions, worth 6 points apiece. You must complete them all in order to be eligible to use this as final exam points.
So long story short—it’s worth your time to complete this assignment!

These questions pertain to the same data set you used for the first SPSS assignment. (I’ve also posted it in the final exam module).

We can see that mean spending for male is higher as compare to female. The p-value of equal variance t test is 0.370 which is bigger than 0.05, so we can conclude that statistically male and female spend same money in a month on restaurants. There is no statistically significant difference in the mean spending in a month on restaurants between male and female.

Prefer Waterfront View and Prefer Drive Less than 30 Minutes are negatively associated with each other as the correlation coefficient value is -0.805 which is a negative value and statistically significant at 5% level of significance.

For respondents with ONLY a Bachelor’s Degree, which 2 preference variables (from the 10 starting with “Prefer”) would you think are the most likely to have statistically significant different means? Why? (Please note that you could actually do this analysis using “Select Cases” and choosing subjects with that variable level for Bachelor’s. I’m not asking you to do this! I’m just saying if you look at the means and had to “guess” which one to further analyze vs. another, which pair would you pick and why?)

The measure for the central tendency (mean) is 28.6988 and for the variability is 94.491 of females’ “expected price of an average evening entrée item alone”.

Let’s say you want to do a sub-group analysis (in other words, dig deeper) on the preferences of respondents who read the newspaper versus people who don’t read the newspaper. What tells you this is probably not a good idea (in other words, why would Professor Mayer say “THIS IS NOT A GOOD DATASET FOR THAT!”)