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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
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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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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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df
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MS
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3.550325
3.550325
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4
0.224675
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5
3.775 Annie's sample size is __________.
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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
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3.550325
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0.224675
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Q:
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Q:
In the regression equation, y=2.164+1.3657x n=6, the mean of x is 8.667, Sxx=89.333 and Se=3.44. A 95% prediction interval for y when x=8 is _________
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Q:
In a regression analysis if SST = 200 and SSR = 200, r 2 = _________.
a) 0.25
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Q:
The proportion of variability of the dependent variable accounted for or explained by the independent variable is called the _______.
a) sum of squares error
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Q:
The numerical value of the coefficient of determination must be _______.
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 _______.
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Q:
The following residuals plot indicates _______________. a) a nonlinear relation
b) a nonconstant error variance
c) the simple regression assumptions are met
d) the sample is biased
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