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.