MATLAB: An Introduction with Applications
6th Edition
ISBN: 9781119256830
Author: Amos Gilat
Publisher: John Wiley & Sons Inc
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- The owner of Showtime Movie Theaters, Inc., would lke to predict weekly gross revenue as a function of advertising expenditures Historical data for a sample of eight wecks follow Weekly Gross Revenue ($1,000s) Television Advertising ($1,000s) Newspaper Advertising ($1,000s) 96 5.0 1.5 90 2.0 2.0 95 4.0 1.5 92 2.5 2.5 95 3.0 3.3 94 3.5 2.3 94 2.5 4.2 94 3.0 2.5 The owner then used multiple regression analysis to predict gross revenue (y), in thousands of dollars, as a function of television advertising (x), in thousands of dolars, and newspaper advertising (x,), in thousands of dollars. The estimated regression equation was = 83.2 + 2.29x, + 1.30x. (a) What is the gross revenue (in dollars) expected for a week when $5,000 is spent on television advertising (x5) and $1,500 is spent on newspaper advertising (, 1.5)? (Round your answer to the nearest dollar.) $06600 (b) Provide a 95% confidence interval (in dolars) for the mean revenue of all weeks with the expenditures listed in part (a).…arrow_forwardSara creates a box plot using 23,26,44,19,31,39, and 43 . Which one shows the data?arrow_forwardUse this data which give the dosage levels for a particular drug and the heart rate measured 30 minutes after taking the drug. Dose (mg) Heart rate 0.125 95 0.20 90 0.25 93 0.30 92 0.35 88 0.40 80 0.50 82 Create a scatter plot. Use your Ti-84arrow_forward
- Is the variable(foot print) below normally distributed or skewed? If skewed, indicate the direction. male shoe print #1 32.2 #2 30.1 #3 29.0 #4 31.8 #5 29.4arrow_forwardThe ordered pairs below give the winning times (in seconds) of a 100-meter freestyle swim race at a regularly-held competition from 1984 through 2012. (1984, 55.12) (2000, 53.03) (1988, 54.13) (2004, 53.04) (1992, 53.84) (2008, 52.32) (1996, 53.70) (2012, 52.20) (a) Sketch a scatter plot of the data. Let y represent the winning time (in seconds) and let t = 84 represent 1984. (b) Sketch the line that you think best approximates the data and find an equation of the line. (Round the slope and y-intercept to one decimal place.) y = (c) Use the regression feature of a graphing utility to find the equation of the least squares regression line that fits the data. (Round the slope and y-intercept to two decimal places.) y = (d) Compare the linear model you found in part (b) with the linear model you found in part (c). The models are not similar.The models are similar.arrow_forwardFind the mean of the data summarized in the given frequency distribution. Compare the computed mean to the actual mean of 51.9 miles per hour. Speed (miles per hour) Frequency 42 - 45 46-49 50 - 53 54 -57 58 -61 25 15 The mean of the frequency distribution is miles per hour. (Round to the nearest tenth as needed.)arrow_forward
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