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Question
Louis Katz, a cost accountant at Papalote Plastics, Inc. (PPI), is analyzing the manufacturing costs of a molded plastic telephone handset produced by PPI. Louis's independent variable is production lot size (in 1,000's of units), and his dependent variable is the total cost of the lot (in $100's). Regression analysis of the data yielded the following tables.| Coefficients | Standard Error | t Statistic | p-value | |
| Intercept | 3.996 | 1.161268 | 3.441065 | 0.004885 |
| x | 0.358 | 0.102397 | 3.496205 | 0.004413 |
| Source | df | SS | MS | F | Se = 0.898 | |
| Regression | 1 | 9.858769 | 9.858769 | 12.22345 | r2 = 0.526341 | |
| Residual | 11 | 8.872 | 0.806545 | |||
| Total | 12 | 18.73077 |
The correlation coefficient between Louis's variables is ________________.
a) -0.73
b) 0.73
c) 0.28
d) -0.28
e) 0.00
Answer
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Related questions
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Q:
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2
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3.19 Total
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Q:
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22
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23
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Q:
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2
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27 26
22
29 23
21
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23
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Q:
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Q:
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97280
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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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4
0.224675
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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
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-0.14156
0.292143
-0.48455
0.653331 x
0.105195
0.013231
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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 Annie's sample size is __________.
a) 2
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c) 6
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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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-0.14156
0.292143
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1
3.550325
3.550325
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0.224675
0.056169 Total
5
3.775 Annie's regression model can be written as: __________.
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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:
A researcher has developed a regression model from fourteen pairs of data points. He wants to test if the slope is significantly different from zero. He uses a two"‘ tailed test and a = 0.01. The critical table t value is _______.
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Q:
In a regression analysis if SST = 200 and SSR = 200, r 2 = _________.
a) 0.25
b) 0.75
c) 0.00
d) 1.00
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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 _______.
a) coefficient of determination
b) sum of squares of error
c) standard error of the estimate
d) R-squared
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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
e) the sample is random