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 sixteen randomly selected days during the past year are given below. These data are plotted in the scatter plot in Figure 1. Also given is the product of the temperature and the coffee sales for each of the sixteen days. (These products, written in the column labelled "xy", may aid in calculations.) Temperature, (in degrees Fahrenheit) 74.9 47.1 72.1 56.7 77.5 39.2 67.5 52.6 72.7 50.0 41.6 81.0 45.0 57.8 48.1 62.6 Send data to calculator 0 Coffee sales, y (in dollars) 1977.4 2013.7 1946.3 1604.0 1519.5 1998.3 1722.2 1823.9 1691.4 2200.7 2270.8 1556.5 1729.6 1966.3 2139.9 1811.9 xy 148,107.26 94,845.27 140,328.23 90,946.8 117,761.25 78,333.36 116,248.5 95,937.14 122,964.78 110,035 94,465.28 126,076.5 77,832 113,652.14 102,929.19 113,424.94 Coffee sales (in dollars) Figure 1 2400 2200 2000 1800 1600- 1400 1200 11 40 50 60 70 80 Temperature (in degrees Fahrenheit) 90 What is the slope of the least-squares regression line for these data? Carry your intermediate computations to at least four decimal places and round your answer to at least two decimal places. (If necessary, consult a list of formulas.)
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 sixteen randomly selected days during the past year are given below. These data are plotted in the scatter plot in Figure 1. Also given is the product of the temperature and the coffee sales for each of the sixteen days. (These products, written in the column labelled "xy", may aid in calculations.) Temperature, (in degrees Fahrenheit) 74.9 47.1 72.1 56.7 77.5 39.2 67.5 52.6 72.7 50.0 41.6 81.0 45.0 57.8 48.1 62.6 Send data to calculator 0 Coffee sales, y (in dollars) 1977.4 2013.7 1946.3 1604.0 1519.5 1998.3 1722.2 1823.9 1691.4 2200.7 2270.8 1556.5 1729.6 1966.3 2139.9 1811.9 xy 148,107.26 94,845.27 140,328.23 90,946.8 117,761.25 78,333.36 116,248.5 95,937.14 122,964.78 110,035 94,465.28 126,076.5 77,832 113,652.14 102,929.19 113,424.94 Coffee sales (in dollars) Figure 1 2400 2200 2000 1800 1600- 1400 1200 11 40 50 60 70 80 Temperature (in degrees Fahrenheit) 90 What is the slope of the least-squares regression line for these data? Carry your intermediate computations to at least four decimal places and round your answer to at least two decimal places. (If necessary, consult a list of formulas.)
MATLAB: An Introduction with Applications
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ISBN:9781119256830
Author:Amos Gilat
Publisher:Amos Gilat
Chapter1: Starting With Matlab
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Transcribed Image Text: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 sixteen randomly selected days during the past year are given below. These data are
plotted in the scatter plot in Figure 1. Also given is the product of the temperature and the coffee sales for each of the
sixteen days. (These products, written in the column labelled "xy", may aid in calculations.)
Temperature,
(in degrees
Fahrenheit)
74.9
47.1
72.1
56.7
77.5
39.2
67.5
52.6
72.7
50.0
41.6
81.0
45.0
57.8
48.1
62.6
Send data to calculator
Coffee sales,
y
(in dollars)
7
1977.4
2013.7
1946.3
1604.0
1519.5
1998.3
1722.2
1823.9
1691.4
2200.7
2270.8
1556.5
1729.6
1966.3
2139.9
1811.9
xy
148,107.26
94,845.27
140,328.23
90,946.8
117,761.25
78,333.36
116,248.5
95,937.14
122,964.78
110,035
94,465.28
126,076.5
77,832
113,652.14
102,929.19
113,424.94
Coffee sales
(in dollars)
Figure 1
2400
2200
2000
1800
1600
1400
1200
Ny
X
40
X
50
60
++
70
X
80
Temperature
(in degrees Fahrenheit)
90
What is the slope of the least-squares regression line for these data? Carry your intermediate computations to at least
four decimal places and round your answer to at least two decimal places. (If necessary, consult a list of formulas.)
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