Question
In: Statistics and Probability
Consider the x, y data: x-data (explanatory variables): 10, 15, 20, 25, 30, 35, 40, 45,...
Consider the x, y data:
x-data (explanatory variables):
10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90,
95, 100
y-data (response variables):
1359.9265, 1353.3046, 220.7435, 964.6208, 1861.9920, 1195.3707,
1702.0145, 2002.0900, 1129.1860, 1864.5241, 1444.2239, 2342.5453,
2410.9056, 2766.2245, 2135.2241, 3113.7662, 4311.7260, 3313.1042,
4072.0945
Compute a best fit line to the data. Report:
a. The slope coefficient, β1:
b. The intercept coefficient, β0:
c. The standard error of the residuals
σε:
d. The Adjusted R-squared correlation coefficient,
Adjusted R2:
e. Is the slope coefficient significant at, at least the 95% level
of confidence?
no OR yes
f. Is the intercept coefficient significant at, at least the 95%
level of confidence?
yes OR no
Solutions
orchestra answered 2 years agoRelated Solutions
Consider the x, y data: x-data (explanatory variables): 10, 15, 20, 25, 30, 35, 40, 45,...
Consider the x, y data:
x-data (explanatory variables):
10, 15, 20, 25, 30, 35, 40, 45, 50, 55, 60, 65, 70, 75, 80, 85, 90,
95, 100
y-data (response variables):
1359.9265, 1353.3046, 220.7435, 964.6208, 1861.9920, 1195.3707,
1702.0145, 2002.0900, 1129.1860, 1864.5241, 1444.2239, 2342.5453,
2410.9056, 2766.2245, 2135.2241, 3113.7662, 4311.7260, 3313.1042,
4072.0945
Compute a best fit line to the data. Report:
a. The slope coefficient, β1: ___
b. The intercept coefficient, β0: ___
c. The standard error of the residuals σε: ___
d....
Consider the following data for two variables, x and y. x 22 24 26 30 35...
Consider the following data for two variables, x and
y.
x
22
24
26
30
35
40
y
13
20
34
35
40
36
(a)Develop an estimated regression equation for the data
of the form ŷ = b0 +
b1x. (Round
b0 to one decimal place and
b1 to three decimal places.)
ŷ =
(b)Use the results from part (a) to test for a
significant relationship between x and y. Use
α = 0.05.
Find the value of the test...
Consider the following data for two variables, x and y. x 22 24 26 30 35...
Consider the following data for two variables, x and
y.
x
22
24
26
30
35
40
y
11
20
32
34
39
35
(a)
Develop an estimated regression equation for the data of the
form
ŷ = b0 +
b1x.
(Round b0 to one decimal place and
b1 to three decimal places.)
ŷ =
(b)
Use the results from part (a) to test for a significant
relationship between x and y. Use α =
0.05.
Find the value of...
Consider the following data for two variables, x and y. x 22 24 26 30 35...
Consider the following data for two variables, x and
y.
x
22
24
26
30
35
40
y
12
20
34
36
39
37
(a) Develop an estimated regression equation for the data of the
form ŷ = b0 +
b1x. (Round
b0 to one decimal place and
b1 to three decimal places.)
ŷ =
(b) Use the results from part (a) to test for a significant
relationship between x and y. Use α =
0.05. Find the value of the test...
Consider the following two variables: x y 45 10 23 30 17 48 19 45 41...
Consider the following two variables:
x
y
45
10
23
30
17
48
19
45
41
34
13
27
39
26
37
31
24
38
12
44
What is the correlation between these two variables? Use
Pearson's r, and take your answer to two decimal places.
To what two-tailed critical value of Pearson's r would you
compare this? Use the provided tables, assume alpha, = 0.05, and
express your answer as an absolute value. Round to two decimal
places.
If...
Consider the data. xi 3 12 6 20 14 yi 65 40 45 15 25 The...
Consider the data.
xi
3
12
6
20
14
yi
65
40
45
15
25
The estimated regression equation for these data is
ŷ = 68.25 − 2.75x.
(a)
Compute SSE, SST, and SSR using equations
SSE = Σ(yi −
ŷi)2,
SST = Σ(yi −
y)2,
and
SSR = Σ(ŷi −
y)2.
SSE=SST=SSR=
(b)
Compute the coefficient of determination
r2.
(Round your answer to three decimal places.)
r2
=
Comment on the goodness of fit. (For purposes of this exercise,...
Consider the data. xi 3 12 6 20 14 yi 55 35 45 10 15 The...
Consider the data.
xi
3
12
6
20
14
yi
55
35
45
10
15
The estimated regression equation for these data is ŷ =
62.25 − 2.75x.
(a) Compute SSE, SST, and SSR using equations SSE =
Σ(yi −
ŷi)2, SST =
Σ(yi −
y)2, and SSR =
Σ(ŷi −
y)2.
SSE=
SST=
SSR=
(b) Compute the coefficient of determination
r2.(Round your answer to three decimal
places.)
r2 =
Comment on the goodness of fit. (For purposes of this...
Consider the following data for two variables, x and y. x 10 34 20 11 24...
Consider the following data for two variables, x and y.
x
10
34
20
11
24
y
11
30
22
19
21
a. Develop an estimated regression equation for
the data of the form y=b0+b1x. Comment on the
adequacy of this equation for predicting . Enter negative value as
negative number.
The regression equation is
Y=___________+___________ (to 2 decimals)
s=__________ (to 3 decimals)
r2=_________% (to 1 decimal)
r2 adj=_______ % (to 1 decimal)
Analysis of Variance
SOURCE
DF
SS
(to...
Given the following table: Probability X Y 20% 15% 30% 60% 25% 18% 20% 30% 20%...
Given the following table:
Probability X Y
20% 15% 30%
60% 25% 18%
20% 30% 20%
Calculate a) the covariance of X and Y, and b) the correlation
coefficient.
Select one:
a. a) -20.64% b) -0.90
b. a) -20.18% b) -0.88
c. a) -17.89% b) -0.78
d. a) -19.20% b) -0.84
e. a) -18.35% b)-0.80
TRAINING EXPENSE (Y) ADMISSION (X) 3 35 1 15 2 20 4 45 A. DETERMINE THE...
TRAINING EXPENSE (Y)
ADMISSION (X)
3
35
1
15
2
20
4
45
A. DETERMINE THE CORRELATION CO-EFFICIENT
B. DETERMINE THE STANDARD ERROR OF THE ESTIMATE FOR THE SIMPLE
REGRESSION
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