Mountain Dew versus Mountain Lightning

1. Mountain Dew versus Mountain Lightning Michael J. Barattini Zack Jensen Doug Doolen Jesse Beecher

2. Many people believe they prefer Mountain Dew over the generic brands such as Mountain Lightning, or Mountain Frost. But do they really? Like the Pepsi test, we decided to choose a random sample of people to drink two small glasses, one filled with the name brand Mountain Dew, and the other filled with the Wal-Mart generic brand Mountain Lightning. Do women prefer one over the other? And do men prefer the opposite? Or does everyone, overall, prefer the same? Common sense, media, and bias would tell us that most people prefer Mountain Dew. Therefore, our null hypothesis becomes H0: People prefer Mountain Dew. Then, our alternate hypothesis becomes H1: People prefer Mountain Lightning. Our sample was chosen by convenience sampling. Normally, convenience sampling does not work in the favor of statistical tests because of the possibility of skewing the data. However, in this case, it doesn’t matter who takes the test, it only matters that they are divided equally amongst men and women. Tests have shown that people over the age of 74 lose a dramatic amount of taste buds (http://hubel.sfasu.edu/courseinfo/SL99/effectage.html), and therefore are not susceptible to certain flavors. We did not test anyone over the age of 74, because it may have skewed the data. Family members, friends, and anyone we could track down who was willing to take the test became our sample data. Other than the age limit, taste buds stay more or less the same throughout a person’s lifetime, and therefore it did not matter that we used convenience sampling. Introduction

3. Data Collected 27 males and 27 females were tested through convenience sampling. We found that the overall preference was Mountain Dew, but also found that more women preferred Mountain Lightning than men, but more men preferred Mountain Dew than women.

4. Procedure Each person was given two small Dixie cups filled with a small sample of Mountain Dew and Mountain Lightning with the contents of each cup kept secret (the cups labeled “A” and “B”). They tasted each cup in whatever order they wanted and determined which they preferred. We then recorded our data onto a spreadsheet marking down their gender, and their preference, and recorded it onto the following graph.

5. E= zcp(1 – p) n = 1.645 .59(.41) 54 = .11 (11%) p-hat = r/n (number of successes [mountain dew preference] over total number of trials) = 32/54 = .5926 = 59% q-hat = 1 – p-hat = 1 – .5926 = .4074 = 41% p= 51% (>50% - null hypothesis) Confidence Level: 90% (.90) Level of Significance:α=.05 s= (p(1-p)) n = (.59)(.41) 54 = .0669 z= p-hat – p pq/n = .59-.51 .0669 = 1.14 = 1.271

6. When looked up on the Standard Normal Distribution Chart, 1.14 has a value of .8729. We subtracted this number from 1 (one tailed – right tailed area) so that we could get a number to compare to our level of significance (α= .05). z= p-hat – p pq/n = .59-.51 .0669 = 1.14 1 – .8729 = .1271 .8729 1.14 .1271 is greater than .05 (level of significance) and we can therefore accept our null hypothesis that states H0: People prefer Mountain Dew.

7. Conclusion Because our data was designed more like a poll, it was necessary to find an alternative route in finding our standard deviation and ultimately proving our null hypothesis. We therefore used the formula s= (p(1-p))/n to find the sample standard deviation. In the end, after using a confidence level of 90%, our z-value was greater than our level of significance (α= .05) and our null hypothesis (H0: People prefer Mountain dew) was confirmed. There are many lurking variables in this experiment, such as how fast a person drank the sample of soda, what time of day, how much they drank, was the taste of the first sample left in their mouth before they tasted the second sample, etc. We found that both men and women prefer Mountain Dew, but that more men preferred Mountain Dew over women and more women preferred Mountain Lightning over men. Note: This study was conducted by a high school statistics class with a relatively small sample size and therefore, while the test was conducted consciously to avoid inaccuracies, the data could be somewhat skewed. Had a larger sample size been used, the overall outcome may have been far more accurate at valid.