Sweet Potato Weights and Histogram Construction
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The quality assurance department in a plant that manufactures sweet potato puree is monitoring the weights of the sweet potatoes that are shipped to them in lots. They take a small sample of the sweet potatoes in each lot and weigh them, recording the weights. A tech in the QA department has compiled the last 300 measurements into the accompanying Excel sheet. He wants to look at the weights in a histogram so he can get an idea of the distribution of the weights. However, he is not sure how many bins should be used to create an accurate picture of the data.
Questions to answer: 1. The Square Root Choice rule, Rice Rule, and Sturges’ Rule can all be used to determine how many bins (bars) should appear in a histogram for a given data set. Using the data in the Excel sheet, create a histogram using the rule assigned to you in the Sweet Potato Weights Assignment in the Basic Quality Tools module. Post the histogram in the forum with the appropriate title. 2. Look at the histograms created with different rules. What similarities do you see in the shapes? What differences do you see in the shapes? 3. What do you consider the average weight of the sweet potatoes? Explain your answer. 4. How might the shape of these histograms affect how someone would interpret the distribution of sweet potato weights or average sweet potato weight? 5. The 300 measurements were taken from 10 different lots. How might the fact that the sweet potatoes come from different lots affect the shape of the histogram? 6. Should the tech have combined all of the data into one set? Why or why not?