# Skittles Project

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Skittles Project
Michael Cullimore
Math 1040
Skittles Project Part 2
Confidence Interval Estimates
- Confidence Interval: A confidence interval is an indicator of a measurement's precision. It is also an indicator of how stable an estimate is, which is the measure of how close a measurement will be to the original estimate if an experiment is repeated.

The calculations show that we are 99% confident that the true proportion of yellow candies falls between 0.20125 and 0.21275. This is about one-fifth of the candies which does seem quite reasonable since there are five different colors in the bag of skittles. We are 95% confident that the true mean of candies per bag falls between 58.9481 and 61.0119. Using this information, we
The calculations determined that in both cases the claims are rejected. In the case of the claim that 20% of skittles are red, the class proportion of 20.4% red skittles and is found to be unlikely to be correct and therefore is rejected because the calculated p-value is less than the significance level. Also, the claim that the mean number of skittles per bag is 55 is tested against the class mean of 59.98. This is also determined to be unlikely correct and is rejected as well because the calculated test statistic falls within the critical …show more content…
However, due to this project and stats class, the way I think about math has changed. Statistics is very different from the math I have grown up learning, and it felt more real and applicable to me. Statistics is something I can use in my everyday life, and I am better able to see where these applications can take place. The skittle’s project really helped convince me that math is used to make sense of all kinds of things, whether it be a math problem, different clinical trials, or food. This class has taught me skills that will be useful in both future math classes, content specific classes, and life in general. A few skills I have been able to gain through this project and course would include ways to organize information, how to make sense of all different kinds of raw data, how to present ideas and results, and how to apply statistics in any

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