f you can can you show me in Excel? That is my question for 25 students Below you are given the examination scores of 25 students. 52 99 83 82 84 23 25 76 90 88 19 78 75 79 80 89 73 74 86 99 a. Calculate the mean for this data. b. Calculate a trimmed mean eliminating the obvious outliers. c. Now calculate the median for the data. Which of the above calculations do you regard as the best measure of ‘average’ class performance? Explain why
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If you can can you show me in Excel? That is my question for 25 students
Below you are given the examination scores of 25 students.
52 99 83 82 84
23 25 76 90 88
19 78 75 79 80
89 73 74 86 99
a. Calculate the mean for this data.
b. Calculate a trimmed mean eliminating the obvious outliers.
c. Now calculate the median for the data.
Which of the above calculations do you regard as the best measure of ‘average’ class performance? Explain why.
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- Management of a home appliance store would like to understand the growth pattern of the monthly sales of Blu-ray disc players over the past two years. Managers have recorded the relevant data in the file P13_33.xlsx. a. Create a scatterplot for these data. Comment on the observed behavior of monthly sales at this store over time. b. Estimate an appropriate regression equation to explain the variation of monthly sales over the given time period. Interpret the estimated regression coefficients. c. Analyze the estimated equations residuals. Do they suggest that the regression equation is adequate? If not, return to part b and revise your equation. Continue to revise the equation until the results are satisfactory.An antique collector believes that the price received for a particular item increases with its age and with the number of bidders. The file P13_14.xlsx contains data on these three variables for 32 recently auctioned comparable items. Estimate a multiple regression equation using the given data. Interpret each of the estimated regression coefficients. Is the antique collector correct in believing that the price received for the item increases with its age and with the number of bidders? Interpret the standard error of estimate and the R-square value for these data.Do the sales prices of houses in a given community vary systematically with their sizes (as measured in square feet)? Answer this question by estimating a simple regression equation where the sales price of the house is the dependent variable, and the size of the house is the explanatory variable. Use the sample data given in P13_06.xlsx. Interpret your estimated equation, the associated R-square value, and the associated standard error of estimate.