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Question
A multiple regression analysis produced the following tables.| Predictor | Coefficients | Standard Error | t Statistic | p-value |
| Intercept | -139.609 | 2548.989 | -0.05477 | 0.957154 |
| x1 | 24.24619 | 22.25267 | 1.089586 | 0.295682 |
| x2 | 32.10171 | 17.44559 | 1.840105 | 0.08869 |
| Source | df | SS | MS | F | p-value |
| Regression | 2 | 302689 | 151344.5 | 1.705942 | 0.219838 |
| Residual | 13 | 1153309 | 88716.07 | ||
| Total | 15 | 1455998 |
Using a = 0.01 to test the null hypothesis H0: b2 = 0, the critical t value is ____.
a) 1.174
b) 2.093
c) 2.131
d) 4.012
e) 3.012
Answer
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Related questions
Q:
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a) increase the sample size
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d) maintain status quo
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a) fail to reject the null hypothesis
b) reject the null hypothesis
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Q:
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Q:
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Q:
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Q:
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Q:
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c) a quantitative variable
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Q:
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Q:
The mean square error (MSerr) is calculated by dividing the sum of squares error (SSerr) by the number of error degrees of freedom (dferr).
Q:
Annie Mikhail, market analyst for a national company specializing in historic city tours, is analyzing the relationship between the sales revenue from historic city tours and the size of the city. She gathers data from six cities in which the tours are offered. Annie's dependent variable is annual sales revenues and her independent variable is the city population. Regression analysis of the data yielded the following tables. Coefficients
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0.292143
-0.48455
0.653331 x
0.105195
0.013231
7.950352
0.001356 Source
df
SS
MS
F Se = 0.237 Regression
1
3.550325
3.550325
63.20809 r2 = 0.940483 Residual
4
0.224675
0.056169 Total
5
3.775 For a city with a population of 500,000, Annie's model predicts annual sales of ________________.
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d) $52,597
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Q:
Annie Mikhail, market analyst for a national company specializing in historic city tours, is analyzing the relationship between the sales revenue from historic city tours and the size of the city. She gathers data from six cities in which the tours are offered. Annie's dependent variable is annual sales revenues and her independent variable is the city population. Regression analysis of the data yielded the following tables. Coefficients
Standard Error
t Statistic
p-value Intercept
-0.14156
0.292143
-0.48455
0.653331 x
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7.950352
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df
SS
MS
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1
3.550325
3.550325
63.20809 r2 = 0.940483 Residual
4
0.224675
0.056169 Total
5
3.775 Annie's sample size is __________.
a) 2
b) 4
c) 6
d) 8
e) 10
Q:
Annie Mikhail, market analyst for a national company specializing in historic city tours, is analyzing the relationship between the sales revenue from historic city tours and the size of the city. She gathers data from six cities in which the tours are offered. Annie's dependent variable is annual sales revenues and her independent variable is the city population. Regression analysis of the data yielded the following tables. Coefficients
Standard Error
t Statistic
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0.105195
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SS
MS
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1
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4
0.224675
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5
3.775 Annie's regression model can be written as: __________.
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Q:
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Q:
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b) (2.75, 23.43)
c) (10.31, 15.86)
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e) (12.09, 14.09)
Q:
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Q:
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Q:
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Q:
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a) between -1 and +1
b) between -1 and 0
c) between 0 and 1
d) equal to SSE/(n-2)
e) between -100 and +100
Q:
A standard deviation of the error of the regression model is called the _______.
a) coefficient of determination
b) sum of squares of error
c) standard error of the estimate
d) R-squared
e) coefficient of correlation
Q:
The following residuals plot indicates _______________. a) a nonlinear relation
b) a nonconstant error variance
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Q:
For the following scatter plot and regression line, at x = 35 the residual is _______.a) positiveb) zeroc) negatived) imaginarye) unknown
Q:
For a certain data set the regression equation is y = 29 - 5x. The correlation coefficient between y and x in this data set _______.
a) must be 0
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d) is positive
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Q:
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a) reject the null hypothesis 12 = 22
b) reject the null hypothesis 12 < 22
c) do not reject the null hypothesis 12 = 22
d) do not reject the null hypothesis 12 < 22
e) do nothing
Q:
Collinsville Construction Company purchases steel rods for its projects. Based on previous tests, Claude Carter, Quality Assurance Manager, has recommended purchasing rods from Redding Rods, Inc. (population 1), rather than Stockton Steel (population 2), since Redding's rods had less variability in length. Recently, Stockton revised it rod shearing operation, and Claude has sampled the outputs from Redding's and Stockton's rod manufacturing processes. The results for Redding were s12= 0.10 with n1= 8, and, for Stockton, the results were s22= 0.05 with n2= 10. Assume that rod lengths are normally distributed in the population If a= 0.05, the appropriate decision is ________.
a) reject the null hypothesis 12 = 22
b) reject the null hypothesis 12 < 22
c) do not reject the null hypothesis 12 = 22
d) do not reject the null hypothesis 12 < 22
e) do nothing
Q:
Collinsville Construction Company purchases steel rods for its projects. Based on previous tests, Claude Carter, Quality Assurance Manager, has recommended purchasing rods from Redding Rods, Inc. (population 1), rather than Stockton Steel (population 2), since Redding's rods had less variability in length. Recently, Stockton revised it rod shearing operation, and Claude has sampled the outputs from Redding's and Stockton's rod manufacturing processes. The results for Redding were s12= 0.10 with n1= 8, and, for Stockton, the results were s22= 0.05 with n2= 10. Assume that rod lengths are normally distributed in the population. If a= 0.05, the critical Fvalue is _____________.
a) 3.68
b) 3.29
c) 3.50
d) 3.79
e) 3.99
Q:
A random sample of 400 items from a population shows that 160 of the sample items possess a given characteristic. A random sample of 400 items from a second population resulted in 110 of the sample items possessing the characteristic. Using this data, a 99% confidence interval is constructed to estimate the difference in population proportions which possess the given characteristic. The resulting confidence interval is _______.
a) 0.06 to 0.19
b) 0.05 to 0.22
c) 0.09 to 0.16
d) 0.04 to 0.21
e) 0.05 to 0.23
Q:
A researcher is interested in estimating the difference in two population proportions. A sample of 400 from each population results in sample proportions of .61 and .64. A 90% confidence interval for the difference in the population proportions is _______.
a) -0.10 to 0.04
b) -0.09 to 0.03
c) -0.11 to 0.05
d) -0.07 to 0.01
e) -0.08 to 0.12
Q:
Maureen McIlvoy, owner and CEO of a mail order business for wind surfing equipment and supplies, is reviewing the order filling operations at her warehouses. Her goal is 100% of orders shipped within 24 hours. In previous years, neither warehouse has achieved the goal, but the East Coast Warehouse has consistently out-performed the West Coast Warehouse. Her staff randomly selected 200 orders from the West Coast Warehouse (population 1) and 400 orders from the East Coast Warehouse (population 2), and reports that 190 of the West Coast Orders were shipped within 24 hours, and the East Coast Warehouse shipped 372 orders within 24 hours. Assuming = 0.05, the appropriate decision is ___________________.a) do not reject the null hypothesis 1- 2= 0b) do not reject the null hypothesis p1- p2= 0c) reject the null hypothesis 1- 2= 0d) reject the null hypothesis p1- p2= 0e) do not reject the null hypothesis p1- p20
Q:
Maureen McIlvoy, owner and CEO of a mail order business for wind surfing equipment and supplies, is reviewing the order filling operations at her warehouses. Her goal is 100% of orders shipped within 24 hours. In previous years, neither warehouse has achieved the goal, but the East Coast Warehouse has consistently out-performed the West Coast Warehouse. Her staff randomly selected 200 orders from the West Coast Warehouse (population 1) and 400 orders from the East Coast Warehouse (population 2), and reports that 190 of the West Coast Orders were shipped within 24 hours, and the East Coast Warehouse shipped 372 orders within 24 hours. Assuming a= 0.05, the observed zvalue is ___________________.
a) -3.15
b) 2.42
c) 1.53
d) 0.95
e) 1.08