Question
In: Statistics and Probability
bivariate data values for the coffee sales (denoted by y, in dollars) and the maximum temperature...
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 are the products of the temperature values and coffee sales values for each of the sixteen days. (These products, written in the column labelled "xy," may aid in calculations.)
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Answer the following. Carry your intermediate computations to at least four decimal places, and round your answer as specified bel
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Solutions
orchestra answered 2 years agoRelated Solutions
The data below show sales of daily ice cream in thousands of dollars and the temperature...
The data below show sales of daily ice cream in thousands of
dollars and the temperature
in
Fahrenheit for 21 consecutive days in an ice cream shop. Assuming
there is a linear
relationship between the two, find the regression coefficients
using the formulae for αhat
and βhat
(not the Excel regression tool).
Daily
High
Sales Per Store
Temperature
(Thousands of
Day
(Degrees
F)
Dollars)
1
63
1.52
2
70
1.68
3
73
1.80
4
75
2.05
5
80 ...
a) Run a regression analysis on the following bivariate set of data with y as the...
a) Run a regression analysis on the following bivariate set of
data with y as the response variable.
x
y
10.7
81.6
13.7
81.5
36.7
56.5
4
72.1
50.7
23.2
47.6
-4.8
37.3
31.9
24.3
75.2
21.5
59.3
17.2
54.6
23.6
75.5
22.2
60.8
29.3
51
14
63.4
0.2
102.7
30.7
48.2
10.3
74.8
26.5
48.2
23.1
87
Verify that the correlation is significant at an ?=0.05?=0.05.
If the correlation is indeed significant, predict what value (on
average) for the...
8. Run a regression analysis on the following bivariate set of data with y as the...
8. Run a regression analysis on the following bivariate set of
data with y as the response variable.
x
y
27.2
68.2
28.1
66.7
28.7
64.6
30.2
66.4
33.7
69.5
31.8
68.3
30.4
67.8
28.6
65.5
32.5
69.4
34.8
67.9
33.3
67.1
28
66.1
- Find the correlation coefficient and report it accurate to
three decimal places.
r =
- What proportion of the variation in y can be
explained by the variation in the values of x? Report
answer...
Run a regression analysis on the following bivariate set of data with y as the response...
Run a regression analysis on the following bivariate set of data
with y as the response variable.
x
y
15.5
58.8
25.4
62.9
53.7
68.8
46.5
78.6
28.5
57.5
5.7
68.1
-0.4
67.8
43.8
87.7
23.1
64.9
31.3
81.3
48.2
80.1
15.9
71.1
1) Find the correlation coefficient and report it accurate to
three decimal places.
r =
2) What proportion of the variation in y can be
explained by the variation in the values of x? Report
answer as...
Run a regression analysis on the following bivariate set of data with y as the response...
Run a regression analysis on the following bivariate set of data
with y as the response variable.
x
y
81
81.3
92.6
90.8
80.1
94.9
77.8
53.4
89.4
102.9
70.3
38.2
90.2
98
81.4
94.6
94.9
122.4
77.2
42.1
70.6
47.8
71
50.6
Find the correlation coefficient and report it accurate to three
decimal places.
r =
What proportion of the variation in y can be explained by
the variation in the values of x? Report answer as a
percentage...
Run a regression analysis on the following bivariate set of data with y as the response...
Run a regression analysis on the following bivariate set of data
with y as the response variable.
x
y
73
16.1
80
14.9
72.5
8.5
55.8
33.6
54.6
23.4
76.6
26.2
74.6
19.1
40.2
40.6
58.7
25.8
Find the correlation coefficient and report it accurate to three
decimal places.
What proportion of the variation in y can be explained by
the variation in the values of x? Report answer as a
percentage accurate to one decimal place. (If the answer...
Run a regression analysis on the following bivariate set of data with y as the response...
Run a regression analysis on the following bivariate set of data
with y as the response variable. x y 26.1 54.3 28.4 42.5 33.8 50.2
63.4 63.3 64.3 79.4 72.5 76.1 46.2 57.4 70.2 82.1 50.5 64.3 55.4
58.8 40.7 48.5 69.4 57.5 40.4 47.8 45.1 60 64 72.5 50.6 56.9 44.2
65.6 Verify that the correlation is significant at an α = 0.05 . If
the correlation is indeed significant, predict what value (on
average) for the explanatory variable...
Run a regression analysis on the following bivariate set of data with y as the response...
Run a regression analysis on the following bivariate set of data
with y as the response variable.
x
y
58.6
56.3
66.3
72.1
54.8
119.2
57.4
83.2
62.8
74.3
77.6
72.2
71.8
62.2
46.4
77.2
77.4
86.6
60.5
78.4
66.4
131.3
76.4
113.5
68.5
84.2
81.5
102
77.5
136.3
49
12.2
Verify that the correlation is significant at an α=0.05. If the
correlation is indeed significant, predict what value (on average)
for the explanatory variable will give you a value...
Run a regression analysis on the following bivariate set of data with y as the response...
Run a regression analysis on the following bivariate set of data
with y as the response variable. x y 37.2 26.9 66.2 41.4 80.9 37.6
83.7 45 55 31.2 46.3 29.1 82 44.1 71.6 36.1 54.7 29.3 56.4 33.8
Predict what value (on average) for the response variable will be
obtained from a value of 45.1 as the explanatory variable. Use a
significance level of α = 0.05 to assess the strength of the linear
correlation. What is the predicted...
Run a regression analysis on the following bivariate set of data with y as the response...
Run a regression analysis on the following bivariate set of data
with y as the response variable.
x
y
62.4
39.2
62.2
40.4
47.7
68.9
120.5
-36.5
49
37.9
69.1
-9.4
53.2
71.8
66
13.8
87
8.4
92.3
-1.6
70.3
17.8
Verify that the correlation is significant at an α=0.05α=0.05.
If the correlation is indeed significant, predict what value (on
average) for the explanatory variable will give you a value of 67.7
on the response variable.
What is the predicted...
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