Question

The following table compares the completion percentage and interception percentage of 5 NFL quarterbacks.

Completion Percentage | 56 | 57 | 64 | 65 | 66 |
---|---|---|---|---|---|

Interception Percentage | 4.5 | 3 | 2.5 | 2 | 1.5 |

Step 1 of 6: Find the estimated slope. Round your answer to three decimal places.

Step 2 of 6: Find the estimated y-intercept. Round your answer to three decimal places.

Step 3 of 6: According to the estimated linear model, if the value of the independent variable is increased by one unit, then the change in the dependent variable y^ is given by?

Step 4 of 6: Determine if the statement "All points predicted by the linear model fall on the same line" is true or false.

Step 5 of 6: Find the estimated value of y when x=65. Round your answer to three decimal places.

Step 6 of 6: Find the value of the coefficient of determination. Round your answer to three decimal places.

Answer #1

Step 1: Sum of *X* = 308

Sum of *Y* = 13.5

Mean *X* = 61.6

Mean *Y* = 2.7

Sum of squares (*SS _{X}*) = 89.2

Sum of products (

Regression Equation = ŷ =

Step 2: *a* = M_{Y} - *b*M_{X} =
2.7 - (-0.22*61.6) = 16.235

Step 3: This value is same as slope so answer is -0.220

Step 4:

So answer is False

Step 5: Regression equation is

ŷ = -0.220*X* + 16.235

For x=65, y=-0.220**65* + 16.235=1.935

Step 6. *X Values*

∑ = 308

Mean = 61.6

∑(X - M_{x})^{2} = SS_{x} = 89.2

*Y Values*

∑ = 13.5

Mean = 2.7

∑(Y - M_{y})^{2} = SS_{y} = 5.3

*X and Y Combined*

*N* = 5

∑(X - M_{x})(Y - M_{y}) = -19.6

*R Calculation*

r = ∑((X - M_{y})(Y - M_{x})) /
√((SS_{x})(SS_{y}))

r = -19.6 / √((89.2)(5.3)) = -0.901

So coefficient of determination is r^2=0.812

The following table compares the completion percentage and
interception percentage of 5 NFL quarterbacks. Completion
Percentage 61 61 62 65 65 Interception Percentage 4.3 2.9 1.6 1.2
1.2 Table Step 1 of 5 : Calculate the sum of squared errors (SSE).
Use the values b0=35.7312 and b1=−0.5333 for the calculations.
Round your answer to three decimal places.

The following table compares the completion percentage and
interception percentage of 55 NFL quarterbacks.
Completion Percentage Interception Percentage
55 4
61 4
63 3.9
63 3
65 1.1
Step 1 of 5: Calculate the sum of squared errors (SSE). Use the
values b0=15.8545b0=15.8545 and b1=−0.2061b1=−0.2061 for the
calculations. Round your answer to three decimal places
Step 2 of 5: Calculate the estimated variance of errors, s2ese2.
Round your answer to three decimal places
Step 3 of 5: Calculate the estimated...

The following table compares the completion percentage and
interception percentage of 5 NFL quarterbacks.
Completion Percentage
55
57
59
61
62
Interception Percentage
4.1
3.9
3.2
2.8
1.9
Step 1 of 5: Calculate the sum of squared errors (SSE). Use the
values b0=20.6024 and b1=−0.2963 for the calculations. Round your
answer to three decimal places.
Step 2 of 5: Calculate the estimated variance of errors, Round
your answer to three decimal places.
Step 3 of 5: Calculate the estimated variance...

The following table compares the completion percentage and
interception percentage of 5 NFL quarterbacks.
Completion Percentage
55
58
58
60
64
Interception Percentage
4.7
4.3
3.8
3.7
2.8
Step 5 of 5 : Construct the 95% confidence interval
for the slope. Round your answers to three decimal places.
.
Previous Answers
b1 = - 0.2091
b0 = 16.1969
SSE = 0.128
s2e = 0.043
s2b1 = 0.001

The following table compares the completion percentage and
interception percentage of 55 NFL quarterbacks.
Completion Percentage
55
58
58
60
64
Interception Percentage
4.7
4.3
3.8
3.7
2.8
Step 4 of 5 :
Construct the 90% confidence interval for the slope. Round your
answers to three decimal places.
Lower endpoint: ____________
Upper endpoint: ____________
.
Previous Answers:
b1 = -0.2091
b0 = 16.1969
SSE = 0.128
s^2e = 0.043
s^2b1 = 0.001

The table below gives the completion percentage and interception
percentage for five randomly selected NFL quarterbacks. Based on
this data, consider the equation of the regression line,
yˆ=b0+b1xy^=b0+b1x, for using the completion percentage to predict
the interception percentage for an NFL quarterback. Keep in mind,
the correlation coefficient may or may not be statistically
significant for the data given. Remember, in practice, it would not
be appropriate to use the regression line to make a prediction if
the correlation coefficient...

The table below gives the completion percentage and interception
percentage for five randomly selected NFL quarterbacks. Based on
this data, consider the equation of the regression line,
yˆ=b0+b1xy^=b0+b1x, for using the completion percentage to predict
the interception percentage for an NFL quarterback. Keep in mind,
the correlation coefficient may or may not be statistically
significant for the data given. Remember, in practice, it would not
be appropriate to use the regression line to make a prediction if
the correlation coefficient...

The table below gives the completion percentage and interception
percentage for five randomly selected NFL quarterbacks. Based on
this data, consider the equation of the regression line,
yˆ=b0+b1xy^=b0+b1x, for using the completion percentage to predict
the interception percentage for an NFL quarterback. Keep in mind,
the correlation coefficient may or may not be statistically
significant for the data given. Remember, in practice, it would not
be appropriate to use the regression line to make a prediction if
the correlation coefficient...

Price in Dollars 20 30 34 38 45
Number of Bids 4 5 6 7 9
tep 1 of 6:
Find the estimated slope. Round your answer to three decimal
places.
Step 2 of 6:
Find the estimated y-intercept. Round your answer to three
decimal places.
Step 3 of 6:
Determine if the statement "Not all points predicted by the
linear model fall on the same line" is true or false.
Step 4 of 6:
Substitute the values you found...

The table below gives the age and bone density for five randomly
selected women. Using this data, consider the equation of the
regression line, y^=b0+b1x, for predicting a woman's bone density
based on her age. Keep in mind, the correlation coefficient may or
may not be statistically significant for the data given. Remember,
in practice, it would not be appropriate to use the regression line
to make a prediction if the correlation coefficient is not
statistically significant.
Age
41
44...

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