Elementary Statistics
Elementary Statistics
12th Edition
ISBN: 9780321837936
Author: Mario F. Triola
Publisher: PEARSON
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Chapter 14.2, Problem 9BSC
To determine

To obtain: The values of x¯ , R¯ , UCL and LCL values for R chart and x¯ chart.

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2.62 For the period 2001–2008, the Bristol-Myers Squibb Company, Inc. reported the following amounts (in billions of dollars) for (1) net sales and (2) advertising and product promotion. The data are also in the file XR02062.   Source: Bristol-Myers Squibb Company, Annual Reports, 2005, 2008.   Year         Net Sales           Advertising/Promotion 2001       $16.612                     $1.201 2002       16.208                     1.143 2003       18.653                     1.416 2004       19.380                     1.411 2005       19.207                     1.476 2006       16.208                     1.304 2007       18.193                     1.415 2008        20.597                    1.550   For these data, construct a line graph that shows both net sales and expenditures for advertising/product promotion over time. Some would suggest that increases in advertising should be accompanied by increases in sales. Does your line graph support this?
The file P02_26.xlsx lists sales (in millions of dollars) of Dell Computer during the period 1987–1997 (where year 1 corresponds to 1987).      Year Sales 1 69 2 159 3 258 4 389 5 546 6 890 7 2014 8 2873 9 3475 10 5296 11 7759 a. Fit a power and an exponential trend curve to these data. Which fits the data better?     b. Use your part a answer to predict 1999 sales for Dell.    c. Use your part a answer to describe how the sales of Dell have grown from year to year.
The following table shows the average monthly distance traveled (in billion miles) by vehicles on urban highways for five different years. Urban Highways - Average Monthly Distance Traveled by Vehicles (Billion Miles) Years Jan Year 1 4.22 Year 2 4.31 Year 3 4.38 Year 4 4.45 Year 5 4.51 Feb Mar Apr May Jun July Aug Sep Oct Nov Dec 5.32 5.21 5.12 4.92 4.49 4.55 4.49 4.44| 4.39 4.37 4.35 4.68 | 4.74 | 4.79 4.88 4.92 5.44 5.34 5.24 4.98 4.59 4.68 4.65 4.61 5.51 5.36 4.63 4.85 4.89 4.98 5.01 5.41 4.71 4.78 4.82 5.59 5.5 5.41 4.72 4.78 4.79 4.82 5.06 5.11 5.65 5.62 5.49 5.12 4.8 4.88 4.82 4.95 5.12 5.22 5.44 a. Construct a time series plot. What type of pattern exists in the data? b. Use a multiple regression model to develop an equation to account for seasonal effects and any linear trend in the data. To capture seasonal effects, use the dummy variables Jan = 1 if month is January, 0 otherwise; Feb = 1 if month is February, 0 otherwise; ...; Nov = 1 if month is November, 0 otherwise; and…
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