Analysis Of Cereals

Submitted By ktsc222
Words: 1080
Pages: 5

Results Cereal comes in a multitude of varieties. Some are healthy and chalked full of fiber, protein and other key nutrients and some a sugarcoated nothings. One thing that all cereal has in common is that it contains calories. Not all cereals have the same amount of calories, just like not all cereals have the same ingredients. The contents of the cereal must affect the amount of calories that are present, specifically the sugar content. In the cereal data set we are given a sample of 75 different types of cereal. The samples of cereal are separated by their location on the self; top shelf, middle shelf, and bottom shelf. The top shelf cereals are the one that we would consider the more healthy choices, such as: Kashi Go Lean, Fiber One, and Smart Start. The middle shelf cereals are the ones we can consider to be the more popular choices; Frosted Flakes, Fruity Peebles, Special K, etc. The bottom shelf cereals are the ones that we will consider to be the least popular cereals, ones like: Trix, Honey Comb, Corn Flakes, etc. For each of the 75 samples of cereal we are given the variables: servings per box, sugar content, fat content, fiber content, and calories. For this study the main focus will be on the sugar content and the calories. A descriptive statistics was run on the two variables (sugar content and calories). The descriptive statistics gave us the values for N, minimum, maximum, mean, and standard deviation. We know that there is 75 different samples of cereal, so our N is 75. For calories, the range is 60-300. With that range we know that the lowest value for calories within the 75 samples of cereal is 60 and that the highest value is 300. Also we know that all of the other values fall between those two values. The mean for all 75 samples of cereal’s caloric value is 145.33 and the standard deviation is 49.792. With that we know that the average number of calories for the sample of cereals is 145.33 and there is at least one sample of cereal that is 49.792 standard deviations from the mean. For sugar content, the range is 0-19 grams. With that range we know that the lowest value for sugar content within the 75 samples of cereal is 0 grams and the highest value is 19 grams. This also tells us that the other values fall between those two values. The mean for the 75 samples of cereal’s sugar content is 8.43 grams with a standard deviation of 4.685 grams. This tells us that, the average amount of sugar is 8.43 grams and at least one value is 4.685 standard deviations away from the mean. We predicted that the sugar content of cereal would have an affect on it caloric value. From the cereal data set that was provided a correlation analysis was preformed. A correlation analyses was used because this test will tell us if two of the variables have an association. A correlation test will not only tell us if there is an association, but it will also tell us the size (positive, negative, strong, medium, or weak) of the association. We know that this data set needed to be analyzed with a correlation because we are looking for a relationship between the sugar content of the cereals and the cereal’s caloric value. After the correlation analysis was ran, we found that there was a association between the cereal’s sugar content and its caloric value, r(73) = .427, p < .01 (see Figure 1). With the r-value of .427 we can also conclude that there is a positive medium correlation between the two variables. A positive medium correlation means that generally with more of one variable there will also be more of the second variable. We have found that there is an association between the sugar content and caloric values of the samples of cereal. From those results, we know that the data has a medium effect size; the significance has a medium effect. The p value came out to be .000, meaning that the test was significant at the 0.01 level. When making the hypothesis for the study, we made no assumptions on whether we