Question

#8

An article used an estimated regression equation to describe the
relationship between *y* = error percentage for subjects
reading a four-digit liquid crystal display and the independent
variables

*x*_{1} = level of backlight,
*x*_{2} = character subtense,
*x*_{3} = viewing angle, and
*x*_{4} = level of ambient light. From a
table given in the article, SSRegr = 23.1, SSResid = 24, and
*n* = 30.

Calculate the test statistic. (Round your answer to two decimal places.)

F =

Calculate r^{2}

for this model. (Round your answer to three decimal places.)

r^{2} =

Calculate s_{e}

for this model. (Round your answer to three decimal places.)

s_{e} =

Answer #1

In a regression analysis involving 30 observations, the
following estimated regression equation was obtained.
ŷ = 17.6 + 3.8x1 −
2.3x2 +
7.6x3 +
2.7x4
For this estimated regression equation, SST = 1,835 and SSR =
1,800.
(a)At α = 0.05, test the significance of the
relationship among the variables.State the null and alternative
hypotheses.
-H0: One or more of the parameters is not
equal to zero.
Ha: β0 =
β1 = β2 =
β3 = β4 = 0
-H0:...

In a regression analysis involving 30 observations, the
following estimated regression equation was obtained.
ŷ = 17.6 + 3.8x1 −
2.3x2 +
7.6x3 +
2.7x4
For this estimated regression equation, SST =
1,805 and SSR = 1,770
a. Find the value of the test
statistic. (Round your answer to two decimal places.)
_________
b. Suppose variables x1 and
x4 are dropped from the model and the following
estimated regression equation is obtained.
ŷ = 11.1 − 3.6x2 + 8.1x3
Compute...

In a regression analysis involving 30 observations, the
following estimated regression equation was obtained.
ŷ = 17.6 + 3.8x1 − 2.3x2 + 7.6x3 + 2.7x4
For this estimated regression equation, SST = 1,815 and SSR =
1,780. (a) At α = 0.05, test the significance of the relationship
among the variables.
State the null and alternative hypotheses.
H0: β0 = β1 = β2 = β3 = β4 = 0
Ha: One or more of the parameters is not equal to...

19) Use the following linear regression equation to answer the
questions.
x3 = −18.7 +
4.3x1 +
8.6x4 −
1.0x7
(b) Which number is the constant term? List the coefficients with
their corresponding explanatory variables.
constant
x1 coefficient
x4 coefficient
x7 coefficient
(c) If x1 = 5, x4 = -6, and
x7 = 4, what is the predicted value for
x3? (Round your answer to one decimal
place.)
x3 =
(d)
Suppose x1 and x7 were held
at fixed...

In a regression analysis involving 27 observations, the
following estimated regression equation was developed. ŷ =
25.2 + 5.5x1 For this estimated
regression equation SST = 1,550 and SSE = 530.
(a) At α = 0.05, test whether
x1 is significant.State the
null and alternative hypotheses.
H0: β1 ≠ 0
Ha: β1 = 0
H0: β0 ≠ 0
Ha: β0 =
0
H0: β0 = 0
Ha: β0 ≠ 0
H0: β1 = 0
Ha: β1 ≠ 0
Find the value...

In a regression analysis involving 27 observations, the
following estimated regression equation was developed.
ŷ = 25.2 + 5.5x1
For this estimated regression equation SST = 1,600 and SSE =
550.
(a) At α = 0.05, test whether
x1is significant.State the null and
alternative hypotheses.
H0: β0 = 0
Ha: β0 ≠ 0
H0: β0 ≠ 0
Ha: β0 =
0
H0: β1 ≠ 0
Ha: β1 = 0
H0: β1 = 0
Ha: β1 ≠ 0
Find the value...

In a regression analysis involving 27 observations, the
following estimated regression equation was developed.
ŷ = 25.2 + 5.5x1
For this estimated regression equation SST = 1,600 and SSE =
550.
(a) At α = 0.05, test whether
x1 is significant.
State the null and alternative hypotheses.
H0: β0 = 0
Ha: β0 ≠
0H0: β0 ≠ 0
Ha: β0 =
0 H0:
β1 ≠ 0
Ha: β1 =
0H0: β1 = 0
Ha: β1 ≠ 0
Find the value of...

You may need to use the appropriate technology to answer this
question.
In a regression analysis involving 30 observations, the
following estimated regression equation was obtained.
ŷ = 17.6 + 3.8x1 −
2.3x2 +
7.6x3 +
2.7x4
For this estimated regression equation, SST = 1,835 and SSR =
1,790.
(a)
At α = 0.05, test the significance of the relationship
among the variables.
State the null and alternative hypotheses.
H0: One or more of the parameters is not
equal to...

A regression model to predict Y, the state burglary
rate per 100,000 people for 2005, used the following four state
predictors: X1 = median age in 2005,
X2 = number of 2005 bankruptcies,
X3 = 2004 federal expenditures per capita (a
leading predictor), and X4 = 2005 high
school graduation percentage.
(a)
Fill in the values in the table given here for a two-tailed test
at α = 0.01 with 40 d.f. (Negative values should
be indicated by a minus...

Use the following linear regression equation to answer the
questions.
x3 = ?16.6 + 3.7x1 +
8.6x4 ? 1.9x7
If x4 decreased by 2 units, what would we
expect for the corresponding change in
x3?
(e) Suppose that n = 20 data points were used to construct
the given regression equation and that the standard error for the
coefficient of x4 is 0.924. Construct a 90%
confidence interval for the coefficient of x4.
(Round your answers to two decimal places.)...

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