Group 6 Contributions to Powerpoint made by: Jamie Page Aaron Little Tani Hatch Nicholas Mazzarese

Popcorn The Best Cooking Time

Purpose – Why We Care Have you ever thought if “If I cooked the bag of popcorn for longer would all these kernels become the popcorn goodness.” Well we did. And to make it sound professional this is how we discussed it. Our research question is “Is the number of un-popped kernels in a single bag related to the amount of time it is cooked in the microwave?” We would like to find out if more time in the microwave will pop more kernels, and at what point does it start to burn.

Our method of data collection is a complete random design, in which the results are obtained through an experiment, the factors are manipulated to produce desired results, and the selected unit of experimentation is randomly assigned to a treatment. Our first quantitative variable is time. The unit of measurement for this variable is minutes. A few possible values for this first quantitative variable are 1, 2, or 3 minutes.

Study Design – Cont. Our second quantitative variable is popcorn kernels. The unit of measurement for this variable is a discreet count. A few possible values for this second quantitative variable are 19, 11, and 2 kernels. To answer this research question, we will gather data as follows: We will cook a bag of popcorn at different amounts of time, example: 1 minute, and 1 minute 30 seconds. Then we will count and record the number of un-popped kernels in the bag. We will do this until one bag contains no kernels.

The Data Collected Time In Seconds Jamie’s DataNicholas’s Data Tani’s DataAaron’s Data

Variable = Time Mean = 1.75 Standard Devation = Five-Number Summary = 0, 0.75, 1.7, 2.75, 3.5 Range = 3.5 Mode = None Outliers = None

Un-Popped Kernels vs. Time

Variable = Un-popped Kernels Mean = 157 Standard Deviation = Five-Number Summary = 0, 16.5, 105.5, 344, 383 Range = 383 Mode = 154,344,376,383 Outlier = None

Un-Popped Kernels vs. Time

r = Jamie Page

Equation Line: y = -2.09x Jamie Page

Surprises in Data Collection: The data overall was pretty normal, however, there were some odd values that seemed unusual. For example, one time interval increased between 150 and 180 seconds, where the number of kernels actually went up. This was the only instance in the data collection that this was observed. It was also a surprise to observe different levels of variability in each time interval, by member. For example, at the 90 second interval, there was a wide range in data; whereas at the 180 second interval, there was very little range. Jamie Page

Difficulties in Data Collection: One small difficulty in representing the data, was graphing the time variable. All of the data was repetitive and even, and so it was hard to analyze. It was easier to compare the time to the kernels, and get a better analysis that way. It would have been more accurate if we had used random time intervals, with each one being a unique second intervals. For example, 46 seconds, 12 seconds, and 367 seconds. Jamie Page

The data is skewed to the right. The collected data suggests that there was a strong correlation between the correlation coefficient and the critical value for a sample size 30 because the absolute value of r is greater than the critical value. The correlation is so close to -1 that the relationship could be described as strongly negative. As the amount of time that the popcorn is cooked increases, the amount of un-popped kernels decreases. There is a correlation between the amount of time the popcorn and the amount of un-popped kernels. Through this experiment, we were able to answer our question/purpose of study. The number of un-popped kernels is related to the amount of time it is cooked in a microwave.