10:09AAwww-awn.aleks.comO REGRESSION AND CORRELATIONPredictions from the least.Managers of an outdoor coffee stand in Coast City are examining therelationship between (hot) coffee sales and daily temperature, hoping tobe able to predict a day's total coffee sales from the maximumtemperature 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 duringthe past year are given below. These data are plotted in the scatter plotin Figure 1.Temperature, x Coffee sales, y(in degreesFahrenheit)(in dollars)68.31787.638.92311.0240072.91684.0220058.81979.563.41816.4200075.81997.646.92131.771.01973.938.72018.2140053.91597.5120045.91996.175.41501.050.92266.381.71574.5Figure 145.51798.9Send data to ExcelAfter deciding on the appropriateness of a linear model relating coffeesales and maximum temperature, the managers calculate the equationof the least-squares regression line to be =2516.78 – 10.49x. This is the lineshown 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 are the mean of the coffee salesChoose onevalues.2. According to the regression equation, for an increase of one degreein temperature, there is a corresponding decrease of how manydollars in coffee sales?10.493. What was the observed coffee sales value (in dollars) when thetemperature was 68.3 degrees Fahrenheit?1800.3134. From the regression equation, what is the predicted coffee salesvalue (in dollars) when the temperature is 68.3 degrees Fahrenheit?(Round your answer to at least one decimal place.)ExplanationCheckO 2021 McGraw-Hil Education. Al Rights Reserved. Terms of Use I Privacy I Accessibility 4. From the regression equation, what is the predicted coffee salesvalue (in dollars) when the temperature is 68.3 degrees Fahrenheit?(Round your answer to at least one decimal place.)

The provided linear regression model is, y^=2516.78-10.49x

Answered: 4. From the regression equation, what…

4. From the regression equation, what is the predicted coffee sales value (in dollars) when the temperature is 68.3 degrees Fahrenheit? (Round your answer to at least one decimal place.)

MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

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Concept explainers

Correlation

Correlation defines a relationship between two independent variables. It tells the degree to which variables move in relation to each other. When two sets of data are related to each other, there is a correlation between them.

Linear Correlation

A correlation is used to determine the relationships between numerical and categorical variables. In other words, it is an indicator of how things are connected to one another. The correlation analysis is the study of how variables are related.

Regression Analysis

Regression analysis is a statistical method in which it estimates the relationship between a dependent variable and one or more independent variable. In simple terms dependent variable is called as outcome variable and independent variable is called as predictors. Regression analysis is one of the methods to find the trends in data. The independent variable used in Regression analysis is named Predictor variable. It offers data of an associated dependent variable regarding a particular outcome.

Question

10:09
AA
www-awn.aleks.com
O REGRESSION AND CORRELATION
Predictions from the least.
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 Coffee sales, y
(in degrees
Fahrenheit)
(in dollars)
68.3
1787.6
38.9
2311.0
2400
72.9
1684.0
2200
58.8
1979.5
63.4
1816.4
2000
75.8
1997.6
46.9
2131.7
71.0
1973.9
38.7
2018.2
1400
53.9
1597.5
1200
45.9
1996.1
75.4
1501.0
50.9
2266.3
81.7
1574.5
Figure 1
45.5
1798.9
Send data to Excel
After 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 =2516.78 – 10.49x. This is the line
shown in Figure 1.
Answer the following:
1. Fill in the blank: For these data, temperature values that are
greater than the mean of the temperature values tend to be paired
with coffee sales values that are the mean of the coffee sales
Choose one
values.
2. According to the regression equation, for an increase of one degree
in temperature, there is a corresponding decrease of how many
dollars in coffee sales?
10.49
3. What was the observed coffee sales value (in dollars) when the
temperature was 68.3 degrees Fahrenheit?
1800.313
4. From the regression equation, what is the predicted coffee sales
value (in dollars) when the temperature is 68.3 degrees Fahrenheit?
(Round your answer to at least one decimal place.)
Explanation
Check
O 2021 McGraw-Hil Education. Al Rights Reserved. Terms of Use I Privacy I Accessibility

4. From the regression equation, what is the predicted coffee sales
value (in dollars) when the temperature is 68.3 degrees Fahrenheit?
(Round your answer to at least one decimal place.)

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