# Saint GBA334 week 3 quiz (in class) - 90318

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Question 1. 1.

The variable to be predicted is the dependent variable

True

False

(Points : 4)

Question 2. 2.

If computing a causal linear regression model of Y = a + bX and the resultant r2 is very near zero, then one would be able to conclude that

(Points : 4)

Y = a + bX is a good forecasting method.

Y = a + bX is not a good forecasting method.

a multiple linear regression model is a good forecasting method for the data.

a multiple linear regression model is not a good forecasting method for the data.

None of the above

Question 3. 3.

A judgmental forecasting technique that uses decision makers, staff personnel, and respondent to determine a forecast

(Points : 4)

exponential smoothing.

the Delphi method.

jury of executive opinion.

sales force composite.

consumer market survey.

Question 4. 4. Which of the following statements about scatter diagrams is true?

(Points : 4)

Time is always plotted on the y-axis.

It can depict the relationship among three variables simultaneously.

It is helpful when forecasting with qualitative data.

The variable to be forecasted is placed on the y-axis.

It is not a good tool for understanding time-series data.

Question 5. 5.

Which of the following is not classified as a qualitative forecasting model?

(Points : 4)

exponential smoothing

Delphi method

jury of executive opinion

sales force composite

consumer market survey

Question 6. 6.

The correlation coefficient resulting from a particular regression analysis was 0.25. What was the coefficient of determination?

(Points : 4)

0.5

-0.5

0.0625

There is insufficient information to answer the question.

None of the above

Question 7. 7.

Which of the following is a technique used to determine forecasting accuracy?

(Points : 4)

exponential smoothing

moving average

regression

Delphi method

Mean absolute percent error

Question 8. 8.

The condition of an independent variable being correlated to one or more other independent variables is referred to as

(Points : 4)

multicollinearity.

statistical significance.

linearity.

nonlinearity.

The significance level for the F-test is not valid.

Question 9. 9.

A prediction equation for starting salaries (in \$1,000s) and SAT scores was performed using simple linear regression. In the regression printout shown below, what does the coefficient of determination of 0.87425889 mean?

SUMMARY OUTPUT

Regression Statistics

Multiple R

0.935018125

R-Square

0.87425889

0.860287655

Standard Error

3.3072944

Observations

11

ANOVA

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