# SAINT GBA334 module 3 quiz 2

Question 1. Question :

A large school district is reevaluating its teachers’ salaries. They have decided to use regression analysis to predict mean teachers’ salaries at each elementary school. The researcher uses years of experience to predict salary. The resulting regression equation was:

Y = 23,313.22 + 1,210.89X, where Y = salary, X = years of experience

Based on this equation, by how much could a teacher expect his or her salary to increase for every additional tear of service?

\$1,210.89X

\$1,210.89

\$1,210.89 + X

\$23,313.22

Question 2. Question :

Time-series models attempt to predict the future by using historical data.

True False

Question 3. Question :

When the significance level is small enough in the F-test, we can reject the null hypothesis that there is no linear relationship.

True False

:

Question 4. Question :

A scatter diagram is a graphical depiction of the relationship between the dependent and independent variables.

True False

Question 5. Question :

Quiz2_Ques7_correlation_coefficient

Click here to view a pdf of this graphic.

The diagram above illustrates data with a:

negative correlation coefficient.

zero correlation coefficient.

positive correlation coefficient.

none of the above.

Question 6. Question :

An air conditioning and heating repair firm conducted a study to determine if the average outside temperature, thickness of the insulation, and age of the heating equipment could be used to predict the electric bill for a home during the winter months in Houston, Texas. The resulting regression equation was:

Y = 256.89 – 1.45X1 – 11.26X2 + 6.10X3, where Y = monthly cost, X1 = average temperature, X2 = insulation thickness, and X3 = age of heating equipment

Assume December has an average temperature of 45 degrees and the heater is 2 years old with insulation that is 6 inches thick.

What is the forecasted monthly electric bill?

\$111.88

\$127.72

\$136.28

\$205.72

Question 7. Question :

Quiz1_Ques10

A prediction equation for starting salaries (in \$1,000s) and SAT scores was performed using simple linear regression. In the regression printout shown above, what can be said about the level of significance for the overall model?

Click here to view the printout in Excel.

SAT is not a good predictor for starting salary.

The significance level for the intercept indicates the model is not valid.

The significance level for SAT indicates the slope is equal to zero.

The significance level for SAT indicates the slope is not equal to zero.

None of the above can be said about the level of significance.

:

Question 8. Question :

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

Exponential smoothing

Moving average

Regression

Delphi method

Mean absolute percent error

Question 9. Question :

A judgmental forecasting technique that uses decision makers, staff personnel, and respondents to determine a forecast is called:

exponential smoothing.

the Delphi method.

jury of executive opinion.

sales force composite.

consumer market survey.

:

Question 10. Question :

Which of the following statements is false concerning the hypothesis testing procedure for a regression model?

The F-test statistic is used.

The null hypothesis is that the true slope coefficient is equal to zero.

The null hypothesis is rejected if the adjusted r2 is above the critical value

An ? level must be selected.

The alternative hypothesis is that the true slope coefficient is not equal to zero.

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