Question 270053
The regression equation is
Sales1 = - 0.86 + 0.920 Units


Predictor    Coef  SE Coef      T      P
Constant   -0.864    3.265  -0.26  0.799
Units      0.9203   0.4219   2.18  0.066


S = 3.76362   R-Sq = 40.5%   R-Sq(adj) = 32.0%


Analysis of Variance

Source          DF      SS     MS     F      P
Regression       1   67.40  67.40  4.76  0.066
Residual Error   7   99.15  14.16
Total            8  166.55


Unusual Observations

Obs  Units  Sales1    Fit  SE Fit  Residual  St Resid
  1   12.4   17.10  10.55    2.55      6.55      2.37R
  7   11.2    2.90   9.44    2.12     -6.54     -2.10R

R denotes an observation with a large standardized residual.


Predicted Values for New Observations

New
Obs   Fit  SE Fit     90% CI         90% PI
  1  6.50    1.31  (4.03, 8.97)  (-1.05, 14.05)


Values of Predictors for New Observations

New
Obs  Units
  1   8.00






If we use values beyond our data set then
a. the predicted value can be wrong
b. the linear model may not fit the trend 
c. A & B
Ans: c
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9. When we find a variable that is statically significant
a. it allows us to build a model for estimating points 
b. it can referred to as a “driver” of the change
c. A & B
d. it is important based on Bohme’s theory of significance
Ans: I would say "a"
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10.A point estimate for 8 units is
a. 8
b. 6.5
c. 7.36
Ans: Sales(8)=-.86 = 0.92*8 = 6.5
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11. A confidence interval for a sample average of 8 units 
a. 4.72 to 9.56
b. 4.03 to 8.97
c. -1.05 to 14.05
d. 1.15 to 14.05
Ans: 4.03 to 8.97 is the answer for either question 11 or question 12
I would have to read some text material to pin it down.
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12. A confidence interval for a individual point of 8 units
a. 4.72 to 9.56
b. 4.03 to 8.97
c. -1.05 to 14.05
d. 1.15 to 14.05
Ans: See answer to question 11 
Cheers,
Stan H.