MKG 350 SPSS Data Analysis Solution

MKG 350 Fall 2018

Final Exam Optional SPSS Data Analysis Set

Please note the following:

• This assignment is 100% optional
• If you decide to complete it, it’s due before the start of your in-classNamefinal 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.
• This assignment replaces 25 points of the final. Note that you can earn up to 30 points on it—you have a little “slack” where you don’t have to be perfect to earn full test points. But if you do score > 25 pts I’ll add the full amount you earn to the test.
• The final exam will be the same length whether or not you complete this. It will simply be worth less if you do this (question values will be 75% of the listed worth on the test).
• You MUST post both an answers sheet AND your .spv output document to the appropriate links in the final exam module in order to get any credit for this assignment
• If adding this assignment’s points to the scaled down-final would actually HURT your grade I’ll just throw this assignment out for you…in other words, there’s no risk in completing it.
• 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).

Questions:

1. Does one gender spend more money in a month on restaurants than the other? How do you know?

SPSS Output is given below:

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.

2. For the total sample, identify two preference variables (from the 10 starting with “Prefer…”) that are negatively associated with each other.

SPSS Output is given below:

Interpretation:

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.

3. 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 2 preference variables Prefer Simple Décor and Prefer Elegant Decor are the most likely to have statistically significant different means because if one prefer the simple, the chances are that he/she may not prefer the elegant décor.

4. Give me the measure for the central tendency and for the variability of females’ “expected price of an average evening entrée item alone?”

SPSS Output is given below:

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”.

5. 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!”)

Reading newspaper is a good habit but it did not help what type of news a respondent reading and moreover it does not help us to analyze the data. This kind of sub-group analysis is helpful for a higher age category but not for a students because this classification or subgroup analysis will generate a biased results and moreover, we will not get equal number of responded in each sub-group such as who read the newspaper versus people who don’t read the newspaper.