12 May The spreadsheet entitled COMPUTERS Stats consists of the mean monthly assembly cost (AC) and the mean monthly percent of profit (PP) earned by the company for the
The spreadsheet entitled COMPUTERS Stats consists of the mean monthly assembly cost (AC) and the mean monthly percent of profit (PP) earned by the company for the 36 months from 2011-2013 as well as the assembly cost and the monthly percent of profit for the first 36 days of production during January and February of 2015 following a change in Ownership. 1. For AC and PP in the 2015 stats, perform the following computations: Find the mean, median and mode. Find the standard deviation s of this sample week. Create a frequency distribution table with 4 classes. Create a histogram using your frequency table. Draw a boxplot of the assembly costs. Using the results from part a) and b) ) to find what percentage of the 36 days’ AC is within +/- 1 standard deviations of the mean. If 35.4% or more is considered a good percentage of profit, what percentage of the 36 days’ PP are 35.4% or more? If we assume 35.4% or more, what percentage of those profits were accomplished in with an assembly cost of $330 or less? Assuming that the 36 months’ mean AC for the first 36 months is a normal distribution, find the mean and the standard deviation, then use a z-table to find what percent of AC was between $320 and $350 per month. Use the 36 months of statistics to create a scatterplot with AC on the x-axis and PP on the y-axis. Draw in a trend line and calculate the equation for the line of regression. Using this equation from part k), approximate to the nearest whole number the percent of profit that could result from requiring an average assembly cost of $340 during the 36 months and approximate to the nearest cent the assembly cost that would result in producing an average of 34.7% per month during that same 36 months. Using StatCrunch, show that the data you used to establish your sample of sample means for the first semester is normally distributed by creating a Normal Quantile Plot.
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