Question

Suppose a statistician built a multiple regression model for predicting the total number of runs scored by a baseball team during a season. Using data for n=200 samples, the results below were obtained. Complete parts a through d.

Ind. Var.I |
β estimate |
Standard Error |
Ind. Var.. |
β estimate |
Standard Error |

Intercept |
3.75 |
13.19 |
Doubles (x3) |
0.63 |
0.03 |

Walks (x1) |
0.23 |
0.04 |
Triples (x4) |
1.02 |
0.21 |

Singles x2 |
0.42 |
0.05 |
Home Runs (x 5) |
1.59 |
0.05 |

a. Write the least squares prediction equation for y = total number of runs scored by a team in a season.

y=+x1+x2+x3+x4+x5 (Type integers or decimals.)

b. Interpret, practically, β0 and β1 in the model. Which statement below best interprets β0?

A.For a change of β0 in any variable, the runs scored decreases by 1.

B.For a decrease of 1 in any variable, the runs scored changes by β0.

C.For an increase of 1 in any variable, the runs scored changes by β0.

D.For a change of β0 in any variable, the runs scored increases by 1.

E.This parameter does not have a practical interpretation.

Which statement below best interprets β1?

A.For a change of β1 in the number of walks, the runs scored increases by 1.

B.For an increase of 1 in the number of walks, the runs scored changes by β1.

C.For a change of β1 in the number of walks, the runs scored decreases by 1.

D.For a decrease of 1 in the number of walks, the runs scored changes by β1.

E. This parameter does not have a practical interpretation.

c. Conduct a test of H0: β3=0 against Ha: β3>0 at α=0.01 The test statistic is (_______).(Round to three decimal places as needed.)

The p-value is (________)(Round to three decimal places as needed.)

▼

(Reject Do not reject) the null hypothesis. There

▼

(is not, is) sufficient evidence to support the alternative hypothesis.d. Form a 90% confidence interval for β5.

Interpret the results. (______, __________),Round to three decimal places as needed.)

Interpret this interval.

We are(________)% confident that the true value of β5 lies in this interval. (Type a whole number.)

Answer #1

b.

Suppose a statistician built a multiple regression model for
predicting the total number of runs scored by a baseball team
during a season. Using data for n=200 samples, the results below
were obtained. Complete parts a through d.
Ind. Var.
β estimate
Standard Error
Ind. Var..
β estimate
Standard Error
Intercept
3.92
13.05
Doubles x3
0.63
0.02
Walks x1
0.22
0.05
Triples x4
1.15
0.17
Singles x2
0.43
0.05
Home runs (x5)
1.54
0.02
a. Write the least squares prediction...

Suppose a statistician built a multiple regression
model for predicting the total number of runs scored by a baseball
team during a season. Use the β
estimates to predict the number of runs scored by a team with 337
walks, 820 singles, 224 doubles, 27 triples, and 108 home
runs.
Ind. Var.
β estimate
Standard Error
Intercept
3.17
14.06
Walks x1
0.39
0.03
Singles x2
0.41
0.05
Doubles x3
0.65
0.04
Triples x4
1.01
0.17
Home Runs x5
1.52
0.04...

A multiple regression model for predicting total number of runs
scored by a Major League Baseball team during a season. Using data
on all teams over a 9-year period (a sample of n=234), the results
in the following table were obtained.
Independent Variable
Beta estimate
Standard Error
t
Constant
3.70
15.00
0.25
Walks (x1)
0.34
0.02
????
Singles (x2)
0.49
0.03
16.33
Doubles (x3)
0.72
0.05
14.40
Triples (x4)
????
0.19
6.00
Home runs (x5)
1.51
0.05
30.20
Stolen bases...

The following regression output was obtained from a study of
architectural firms. The dependent variable is the total amount of
fees in millions of dollars.
Predictor
Coefficient
SE Coefficient
t
p-value
Constant
9.387
3.069
3.059
0.010
x1
0.232
0.204
1.137
0.000
x2
−
1.214
0.584
−
2.079
0.028
x3
−
0.273
0.424
−
0.644
0.114
x4
0.642
0.362
1.773
0.001
x5
−
0.060
0.028
−
2.143
0.112
Analysis of Variance
Source
DF
SS
MS
F
p-value
Regression
5
2,364.50
472.9...

ADVERTISEMENT

Get Answers For Free

Most questions answered within 1 hours.

ADVERTISEMENT

asked 20 minutes ago

asked 43 minutes ago

asked 49 minutes ago

asked 56 minutes ago

asked 2 hours ago

asked 2 hours ago

asked 2 hours ago

asked 2 hours ago

asked 3 hours ago

asked 3 hours ago

asked 3 hours ago

asked 4 hours ago