Managers of an outdoor coffee stand in Coast City are examining the relationship between (hot) coffee sales and daily temperature, hoping to be able to predicta day's total coffee sales from the maximum temperature that day. The bivariate data values for the coffee sales (denoted by y, in dollars) and the maximumtemperature (denoted by x, in degrees Fahrenheit) for each of fifteen randomly selected days during the past year are given below. These data are plotted in thescatter plot in Figure 1.Temperature, x(in degreesFahrenheit)Coffee sales, y(in dollars)67.31722.954.11596.02400-76.01509.263.01842.6220041.62296.72000-46.92131.51800-46.61805.045.61973.71600--83.41543.91400-70.81952.976.21974.41200-73.41638.158.31906.340506070809051.92245.9Figure 138.81995.2Send data to ExcelContinueSubmit AssignmentO 2021 McGraw-Hill Education. All Rights Reserved. Terms of Use Privacy I Accessibilityype here to search99+3 Send data to ExcelAfter deciding on the appropriateness of a linear model relating coffee sales and maximum temperature, the managers calculate the equation of the least-squares regression line to be y = 2520.75-10.83x. This is the line shown in Figure 1.Answer the following:1. Fill in the blank: For these data, temperature values that aregreater than the mean of the temperature values tend to be pairedwith coffee sales values that arevalues.the mean of the coffee salesChoose one2. According to the regression equation, for an increase of one degreein temperature, there is a corresponding decrease of how manydollars in coffee sales?3. What was the observed coffee sales value (in dollars) when thetemperature was 73.4 degrees Fahrenheit?4. From the regression equation, what is the predicted coffee salesvalue (in dollars) when the temperature is 73.4 degrees Fahrenheit?(Round your answer to at least one decimal place.)ContinueSubmit AssignmO 2021 McGraw-Hill Education. All Rights Reserved. Terms of Use | Privacy AccesO Type here to search99+

It is an important part of statistics. It is widely used.

Managers of an outdoor coffee stand in Coast City are examining the relationship between (hot) coffee sales and daily temperature, hoping to be able to predict a day's total coffee sales from the maximum temperature that day. The bivariate data values for the coffee sales (denoted by y, in dollars) and the maximum temperature (denoted by x, in degrees Fahrenheit) for each of fifteen randomly selected days during the past year are given below. These data are plotted in the scatter plot in Figure 1. Temperature, x (in degrees Fahrenheit) Coffee sales, y (in dollars) 67.3 1722.9 54.1 1596.0 2400- 76.0 1509.2 63.0 1842.6 2200 - 41.6 2296.7 2000- 46.9 2131.5 1800- 46.6 1805.0 45.6 1973.7 1600 83.4 1543.9 1400- 70.8 1952.9 76.2 1974.4 1200- 73.4 1638.1 58.3 1906.3 51.9 2245.9 Figure 1 38.8 1995.2 Send data to Excel Continue Submit Assignment O 2021 McGraw-Hill Education. All Rights Reserved. Terms of Use I Privacy Accessibility pe here to search 99+

Managers of an outdoor coffee stand in Coast City are examining the relationship between (hot) coffee sales and daily temperature, hoping to be able to predict a day's total coffee sales from the maximum temperature that day. The bivariate data values for the coffee sales (denoted by y, in dollars) and the maximum temperature (denoted by x, in degrees Fahrenheit) for each of fifteen randomly selected days during the past year are given below. These data are plotted in the scatter plot in Figure 1. Temperature, x (in degrees Fahrenheit) Coffee sales, y (in dollars) 67.3 1722.9 54.1 1596.0 2400- 76.0 1509.2 63.0 1842.6 2200 - 41.6 2296.7 2000- 46.9 2131.5 1800- 46.6 1805.0 45.6 1973.7 1600 83.4 1543.9 1400- 70.8 1952.9 76.2 1974.4 1200- 73.4 1638.1 58.3 1906.3 51.9 2245.9 Figure 1 38.8 1995.2 Send data to Excel Continue Submit Assignment O 2021 McGraw-Hill Education. All Rights Reserved. Terms of Use I Privacy Accessibility pe here to search 99+

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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