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Dayna Doman
Econ 206
Research Project

1.) My research project aimed to answer questions concerning Kalamazoo College’s housing and living provisions for students. I believe that ones living conditions is a very significant factor in their college experience. As a student, I’ve heard many people’s opinions on the food we eat, the dorms we live in, and the amenities offered for us. Finding out what students think about current housing will identify the problem. In addition, the current housing policy that of Kalamazoo College is critical to the schools unique character. Finding out what students think about current housing identified the problem. From there, I wanted to know what students thought would improve these conditions. This provides insight for a solution. The college is not providing a positive environment if students are not pleased with the current housing at this college and feel forced to live on campus until their senior year. Kalamazoo College should aim to make students want to live on campus as part of a close community. I believe my study will show what would be good investments for Kalamazoo College to make in order to improve student life.
2.) My population of interest was students at Kalamazoo College. Of the 1200 students, I sent surveys out to one hundred. I made 100 survey packets that consisted of the survey, a return envelope labeled “Dayna Doman Box # 175” and a Dum-Dum sucker For my survey, I decided a systematic random sample was ideal. Because my topic concerns student housing, using a convenience sample, such as students in only my dorm, would have led to biased results. I selected my sample by generating a random number between one and fifty to be the starting person, and an additional random number between one and fifteen to be the sequence. By using a random number generator (www.random.org), I started with the 29th person on my list and picked each 8th person. The list I used was the spring quarter 2006 student phone directory. This list includes all enrolled students, both on and off campus. The list is alphabetical, and not sorted by year. Participants were asked to complete the survey, put it in the marked return envelope and send it to my mailbox through student mail. I received thirty-six surveys back, which is a little lower than what I had hoped for, but still significant enough to conduct a well- rounded statistical study. This was a 36% response rate and 3% of the total population. Unfortunately, I cannot say my resulting sample was representative of the population. A majority were females, freshmen and sophomores. This may be because off-campus students do not check their mail center boxes often. Although I did not get a large number of upperclassmen or off-campus students, my sample still included both.

3. A) My descriptive statistics allowed me to see both what students thought about current student housing and what alternative and improvements most appealed to them. The lowest rated aspect of current student housing were, as I anticipated, the cable service and meal plans. The highest rated aspect of current student housing was our internet service, even though the demand for wireless was also the highest. The most appealing alternative housing options were apartment-style dorms and townhouse-style dorms. The least appealing were building on-campus houses and adding programs to integrate off-campus life. The most appealing housing options were cable and wireless internet. The least appealing options were adding long-distance phone plans and putting kitchenettes in dorm rooms. Additionally, the overall mean of current student housing on a scale of one to five was 3.093. I see this as a fairly low overall rating of current housing, and hopefully a good indication to our college that changes should be implemented.
For my results of what students would be willing to pay for alternative housing and housing options, I had to change my data. Students were asked to check off a range of price, such as $100-300. I thought asking them to just write down a price would be confusing and too time consuming for participants. By giving them a range, I only had one person not complete it. However, in order to calculate descriptive statistics, I had to convert each range into one number. Each range was converted into the median of it (so $100-300 became $200). The >$3000 range was converted to $4000 to prevent any extreme values. It is important to note that only one participant checked that price range. I was not surprised to see that people would pay more for new housing than options. I was most surprised that even though students rate cable here very low and find cable very appealing, they weren’t willing to pay too much for it. The mean for cable was $77/year. This may be because students think should be a college investment and not something they need to take full financial responsibility for.
3 B.) I created confidence intervals for the highest and lowest ranking categories of current student housing, alternative student housing and alternative housing options. Each of these has a 95% confidence. Since my sample size was 36, I used the t-value for 40, which is 2.021. Each of these intervals confirms that there is statistical significance in saying that it is the highest or lowest ranking. None on my lowest ranking intervals cross over into the same range of my highest ranking intervals. The standard errors for these six categories were fairly close to each other, ranging from about 0.14 to 0.27. I had originally feared that large standard errors and my smaller sample size would create confidence levels that crossed over and proved that my highest and lowest ranking results could be interchangeable.
Current Housing
HIGH Internet: 3.530-4.246
LOW Cable: 1.468-2.198
Alternative Housing
HIGH Apartment-Style Dorms: 3.906-4.482
LOW Off-Campus Life Programming : 2.866-3.746
Alternative Housing Options
HIGH Cable: 3.955-4.711
LOW Long-Distance Phone Plans: 2.230-3.324

One of my most interesting proportions I found was how many students believe we should allow off-campus housing after their first year of school here and allow students to have no requirement at all for the meal plans. My survey included options for both ranging from after the first quarter of first year to senior year (the current policy). Of thirty-five participants (one didn’t respond), 54.3% thought Kalamazoo College should allow off-campus housing either after the first year or even before the end of first year. Additionally, 25.7% thought the school should allow off-campus housing after sophomore year. 68.6 % of participants thought the school should have no meal plan requirement at all, and 22.8% thought the requirement should only be either before or by the end of the students first year at K. Even after creating confidence intervals with a 95% confidence, my results illustrated that a large proportion of students believed we should have less housing requirements and no meal plan requirement.
Housing Requirement
After First Year 37.8%- 70.8%
After Second Year 11.2%- 40.2%
Meal Plan Requirement
No Requirement 53.2%- 84.0%
After First Year 8.9%-36.8%

3C.) For my first hypothesis testing, I tested my mean of satisfaction with Kalamazoo College life to that of the Princeton review. The variables I used were the ten variables in my “Current Housing” section. The Princeton review uses a 60-99 rating scale and I used a 1-5 scale. This is because of the complexity of my study as compared to that of the Princeton Review. The mean rating of life at Kalamazoo College was 73, which is 13 points up, on a 39 point scale. This is at the 33.3% point along the Princeton Review scale. If I converted this a 1-5 scale, the mean would be 1.67, which is at the 33.3 percentile of my 1-5 scale. I hypothesized that the mean of the Princeton Review would be equal to my mean. Because The Princeton Review did not provide data on a standard error for their calculation, I will be testing to see if I can reject their mean from my own. H null is that the mean is 3.093 , and H alternative is that the mean is not 3.093.
My equation was 3.093 +/- 2.021 (.63275) , which led to a critical region of 1.814 to 4.372. Although it came fairly close, I can reject The Princeton Reviews calculation of 1.67. It is important to note that their study was probably conducted with more participants in a population not exact to my own (it’s an older study). Additionally, the factors used to measure a rating of campus life for each study were similar, but not identical.
My second hypothesis was to compare my results of the proportion of students saying they live off campus, the percent of males and females, and the mean GPA from my study to that actually reported for the college. The Princeton Review last recorded that 26% of students live off campus and that 57% are female. A fiftey-student survey I found online stated that “Kalamazoo College students surveyed reported having an average GPA of 3.33 with a standard deviation of 0.37.” (Student Spending at Kalamazoo College and Harvard). My sample showed a mean of 3.31, 48.6 % females, and 5.6% of students living off campus. For percent of students living off-campus, my standard error was 7.46%. This gave me a critical region with 95% confidence of -14.62 % to 14.62 %t difference between the two calculations. Because 26-5.6 is 20.4, I can reject the null hypothesis that P1-P2=O. For the percent of females on campus, my standard error was 11.54% which gave me a critical region with 95% confidence of -22.61% to 22.61%. I can not reject the null hypothesis that P1-P2= 0 because 57-47 is 10 and falls within the critical region. For student GPA, my standard error was 0.11. This gave me a critical region with a 95% confidence of -.23 to .23. I can not reject the null hypothesis that x1-x2= 0 because 3.33-3.31 equals .02 and falls within the critical region. I’m glad that I could get at least some demographics close to other studies done. I had expected from the start that I would not get a proportional amount of off-campus students. This is simply because they are less likely to be checking mail in the Hicks Center since they live off-campus.
3E.) I had two multiple regressions that I thought were important for my study. The first was to compare the relation between the satisfaction of current housing ( a mean of all ten ratings for each participant), to the family income of the student, the GPA of the student, and the age of the student. That is, with age, GPA, and family income as a function of satisfaction with current housing. I had 22 participants that had answered both their GPA and annual family income. My equation was Y=.258 x1- 8.044 x2 -0.044 x3 -1.536. This means there was a negative Y-intercept, a slightly positive relationship between age and the satisfaction with the school (+.258), a very negative relationship between satisfaction with the school and income (-8.044), and a negative relationship between GPA and school housing satisfaction. . I expected that older students would be less satisfied with the school, but was wrong. I did think that the more income a student had, the less satisfied they’d be with housing, however not a strong as the regression suggests. This is probably because many students families make over $100,000 a year. I also thought students with a higher GPA would be more satisfied, but was wrong. My R-squared was 0.43, which means the variation isn’t fully explained by the equation, but isn’t completely unexplained either.
My second multiple regression was to see the relation between the appeal of on-campus apartment-style dorms, the amount students were willing to pay (using my conversion earlier stated), and the annual income of the student. This included 26 participants. Apartment-style on-campus dorms were the highest ranking alternative housing option. The regression I calculated was Y=.0011 x1 + 1.082 x 2 + 3.737. There was a very slightly positive relationship between the appeal of the housing option and the willingness to pay (+.0011). This was not what I expected. One would think that the appealing the idea, the more willing a student is to pay for it. I did find a positive relationship between annual income and the appeal of apartment-style dorms. After seeing the negative relationship between satisfaction with current housing and income, this doesn’t surprise me. However, the R-Squared was 0.264, which means the line has a pretty “poor fit” and has a lot of unexplained variation.