DescribingDataAssignment[1] - The Empricial Rule (used...

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QMB 3250 Describing Data Assignment In class, we did some exploratory analysis on the number of bankruptcies by state, which were in the BankruptAndPop.XLS data set. 1. First, recreate the year 2000 bankruptcy rate per 1000 residents by dividing Bkrpt2000 by Pop2000 (the population is already in units of 1000 residents.) 2. Now do the same thing for the 2007 bankruptcies (use the Bkrpt2007 and Pop2007 columns). 3. Analyze the 2007 bankruptcy rates per 1000 residents with the ExploreData.xls template. a. Are there any outliers in this data? Yes b. If so, which states? Tennessee, Georgia, Alabama 4. Compute two- and three-standard deviation intervals from the mean rate. Apply either Chebyshev’s inequality or the empirical rule, whichever you think is more appropriate. Does this appear to be an accurate summary for how many data points lie within the intervals? 2 StDev from Mean: 4.5685 3 StDev from Mean: 5.6421
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Unformatted text preview: The Empricial Rule (used because the data is roughly bell shaped) says that 95% of data lies within 2 standard deviations from the mean and about 99% of data lies within 3 standard deviations from the mean. This rule holds somewhat true in the case of 2007 Bankruptcy Rates per 1000 Residents. 94% (47/50) of the data lies within 2 standard deviations of the mean and 98% (49/50) of the data lies within 3 standard deviations of the mean. 5. According to the histogram, what is the basic shape for the rates per 1000 residents in 2007? Bell shaped 6. Finally compare the 2000 and 2007 rates. The bankruptcy laws were changed in 2007. What was the effect of this on the number of bankruptcies? The Mean in 2007 was 2.271 and the Mean in 2000 was 4.4987. The average number of bankruptcies per 1000 residents went down in 2007 in comparison to 2000....
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This note was uploaded on 02/14/2011 for the course QMB 3250 taught by Professor Thompson during the Spring '08 term at University of Florida.

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DescribingDataAssignment[1] - The Empricial Rule (used...

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