We expect virtually all the data in a stable process to fall within 2 standard deviations of the ...

We expect virtually all the data in a stable process to fall within 2 standard deviations of the mean.
 
  Indicate whether the statement is true or false

Q. 2

A regression model that is deemed to have a regression slope coefficient that could be equal to zero should not be used for prediction since there is no established linear relationship between the x and y variable.
 
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Q. 3

It is possible for the standard error of the estimate to actually increase if variables are added to the model that do not aid in explaining the variation in the dependent variable.
 
  Indicate whether the statement is true or false

Q. 4

In a contingency analysis, the greater the difference between the actual and the expected frequencies, the more likely:
 
  A) H0 should be rejected.
  B) H0 should be accepted.
  C) we cannot determine H0.
  D) the smaller the test statistic will be.

Q. 5

An advantage of exponential smoothing techniques over a regression-based trend model is that the exponential smoothing model allows us to weigh each observation equally, thereby giving a fairer method of developing a forecast.
 
  Indicate whether the statement is true or false

Q. 6

A manufacturing company is interested in predicting the number of defects that will be produced each hour on the assembly line. The managers believe that there is a relationship between the defect rate and the production rate per hour.
 
  The managers believe that they can use production rate to predict the number of defects. The following data were collected for 10 randomly selected hours.
 
  Defects Production Rate Per Hour
  20 400
  30 450
  10 350
  20 375
  30 400
  25 400
  30 450
  20 300
  10 300
  40 300
 
  Given these sample data, the simple linear regression model for predicting the number of defects is approximately = 5.67 + 0.048x.
   Indicate whether the statement is true or false

Q. 7

Standard stepwise regression combines attributes of both forward selection and backward elimination.
 
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Q. 8

The prediction interval developed from a simple linear regression model will be at its narrowest point when the value of x used to predict y is equal to the mean value of x.
 
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