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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 |
Using a = 0.05, Louis should ________________.
a) increase the sample size
b) suspend judgment
c) not reject H0: b1 = 0
d) reject H0: b1 = 0
e) do not reject H0: b0 = 0
Answer
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Related questions
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Q:
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2
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8
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7 Block 2
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Q:
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SS
df
MS
F Treatment
36.17
2
18.08
5.66 Error
28.75
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3.19 Total
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Q:
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2
3 27
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27 26
22
29 23
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27 24
23
26 For a one-way ANOVA, the Error Sum of Squares (SSE) is ________.
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Q:
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2
3 27
26
27 26
22
29 23
21
27 24
23
26 For a one-way ANOVA, the Total Sum of Squares (SST) is ________.
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Q:
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Q:
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Q:
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15
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97280
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Q:
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Q:
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A cost accountant is developing a regression model to predict the total cost of producing a batch of printed circuit boards as a linear function of batch size (the number of boards produced in one lot or batch), production plant (Kingsland, and Yorktown), and production shift (day, and evening). In this model, "shift" is ______.
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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
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MS
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3.550325
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4
0.224675
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5
3.775 For a city with a population of 500,000, Annie's model predicts annual sales of ________________.
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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
0.105195
0.013231
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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 Annie's sample size is __________.
a) 2
b) 4
c) 6
d) 8
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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
-0.48455
0.653331 x
0.105195
0.013231
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 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:
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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
e) -1.00
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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c) coefficient of determination
d) covariance
e) regression sum of squares
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
e) coefficient of correlation
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