The owner of a bicycle store wonders if the employees who take the longest lunch breaks also make the fewest bicycle sales. One day, she notes the length of each salesperson's lunch break (in minutes), x, as well as the number of bicycles he or she sold that day, y. The least squares regression line of this data set is: ý = -0.297x + 10.889 Complete the following sentence: If a salesperson spends one additional minute at lunch, the least squares regression lin predicts he or she will sell | fewer bicycles that day.

The owner of a bicycle store wonders if the employees who take the longest lunch breaks also make the fewest bicycle sales. One day, she notes the length of each salesperson's lunch break (in minutes), x, as well as the number of bicycles he or she sold that day, y. The least squares regression line of this data set is: ý = -0.297x + 10.889 Complete the following sentence: If a salesperson spends one additional minute at lunch, the least squares regression lin predicts he or she will sell | fewer bicycles that day.

Advanced Engineering Mathematics

10th Edition

ISBN:9780470458365

Author:Erwin Kreyszig

Publisher:Erwin Kreyszig

Chapter2: Second-order Linear Odes

Section: Chapter Questions

Problem 1RQ

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Mark Price, the new productions manager for Speakers and Company, needs to find out which variable most affects the demand for their line of stereo speakers. He is uncertain whether the unit price of the product or the effects of increased marketing are the main drivers in sales and wants to use regression analysis to figure out which factor drives more demand for their particular market. Pertinent information was collected by an extensive marketing project that lasted over the past 10 years and was reduced to the data that follow: YEAR SALES/UNIT (THOUSANDS) PRICE $/UNIT ADVERTISING ($000) 1998 395 278 605 1999 695 219 831 2000 895 216 1,104 2001 1,286 207 1,404 2002 1,147 219 1,203 2003 1,180 193 1,286 2004 895 222 884 2005 1,104 202 1,104 2006 974 220 696 2007 1,238 216 884 2008 884 220 696 2009 804 247 696
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The average gestational age (time from conception to birth) of a newborn infant is about 40 weeks. The following data presents the gestational age in weeks and corresponding mean birth weight in pounds for female infants born in Canada. Find the least-squares regression line for predicting the birth weight from the gestational age. You should be able to grab the data in the table, copy it, and paste it in Excel. You would then select the data in Excel, Insert a Scatter Chart and then under Trendline, check the two boxes at the bottom to display the equation and the R-squared. Gestational Age Birth Weight 36 6.1 37 6.6 38 7.0 39 7.4 40 7.7 41 7.9 42 8.0 43 8.1 A. y= 3.2787x + 15.402 B. y= 15.402x + 3.2787 C. y= 0.2857x - 3.9357 D. Y= 3.9357X + 0.2857
For major league baseball teams, do higher player payrolls mean more gate money? Here are data for each of the American League teams in the year 2001 . The variable x denotes the player payroll (in millions of dollars) for the year 2001 , and the variable y denotes the mean attendance (in thousands of fans) for the 81 home games that year. The data are plotted in the Figure 1 scatter plot, as is the least-squares regression line. The equation for this line is =y+13.820.23x . Player payroll, x(in $1,000,000s) Mean attendance, y(in thousands) Anaheim 46.6 24.69 Baltimore 73.4 38.15 Boston 109.6 32.47 Chicago White Sox 62.4 21.85 Cleveland 92.0 39.26 Detroit 49.8 23.70 Kansas City 35.6 19.01 Minnesota 24.4 21.98 New York Yankees 109.8 40.25 Oakland 33.8 26.54 Seattle 75.7 43.33 Tampa Bay 55.0 16.05 Texas 88.5 34.94 Toronto 75.8 23.70 y 5 10 15 20 25 30 35 40 45 x 20 40 60 80 100 120 140 0…
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Biologist Theodore Garland, Jr. studied the relationship between running speeds and morphology of 49 species of cursorial mammals (mammals adapted to or specialized for running). One of the relationships he investigated was maximal sprint speed in kilometers per hour and the ratio of metatarsal-to-femur length. A least-squares regression on the data he collected produces the equation ŷ = 37.67 + 33.18x where x is metatarsal-to-femur ratio and y is predicted maximal sprint speed in kilometers per hour. The standard error of the intercept is 5.69 and the standard error of the slope is 7.94. Construct a 96% confidence interval for the slope of the population regression line. Give your answers precise to at least two decimal places. contact us help 6:42 PM povecy polcy terms of use careers A E O 4») 18 -క90.4 58 12/14/2020 a 17 |耳即 delets prt sc insert 112 19 18 + 16 backspace f5 fA