Unit 4 Dropbox Assignment Answers by (Integer Name)

Unit 4 Dropbox Assignment Answers by (Insert your name here)
In the summary tables below, insert only the answers. You will show work after the
summary section.
Question 1 answers
1a: forecast The regression result for forecasting the rental and leasing
revenue presents the following model:
Rental∧leasing revenue=510579.2143−251.50∗(Year)
The above model is used to predict the rental and leasing
revenue for the year 2011.
Rental∧leasing revenue=510579.2143−251.50∗2011
¿ 4812.7143 ≃4813
Hence, the forecasted rental and leasing revenue for the year
2011 is $4813 million.
1b: reliability The R-squared value of the model is 0.6146 which implies that
61.46% of observed variation can be explained by the model.
The F-stat of the model is 7.9725 and the corresponding p-
value is 0.0370 which indicates that the model has the
predictive capability and better than the constant model.
The reliability test is performed to be confident about the
forecast. Table presents the test result and produces the value
of Cronbach’s alpha. When the value of Cronbach’s alpha is
greater or equal to 0.7 then it can be said that the internal
consistency is acceptable. However, the result table presented
in table 2 shows that the value of Cronbach’s alpha in this
context is negative which is very low and the internal
consistency is at its worst.
Hence, it can be said that the confidence about forecasted
result is very low as the internal consistency is very poor.
Question 2 answers
2a: formula The regression result to predict the job satisfaction presented
in the table 3, presents the following model:
Job satisfaction=98.3291+1.3232∗( Relatioship withsuupervisor )−1.5224∗( Total hours wo
2b: reliability The adjusted R-squared value of the model is 0.7719 that
means 77.19% of the observed variation can be explained by
the model with the help of incorporated independent variable
in the model. The F-stat of the model is 16.2297 and the
corresponding p-value is 0.000 which implies that the model
has the predictive capability and better than the constant
model.
The reliability test for the model is performed and presented
in table 4. The table presents the Cronbach’s alpha value for
the model. The value of Cronbach’s alpha is 0.132 which
shows the very poor internal consistency.
2c: variables There are variables that are included in the model which are

not able to predict the job satisfaction. The variables that
does not appear to be a good predictor, are “opportunities for
advancement” and “overall quality of work environment”.
The regression result table 3 presents the test statistics for
the coefficient of the independent variable and the
corresponding p-values. The t-stat of the coefficient of
“opportunities for advancement” and “overall quality of work
environment” are 0.3732 and -0.6702. The p-values of the
coefficient of “opportunities for advancement” and “overall
quality of work environment” are 0.7146 and 0.5137. This p-
values are greater than 0.05 which indicates that there lack
of evidence in order to reject the null hypothesis of the test.
The null hypothesis says that the mean coefficient of the
variable is not significantly different from zero. In simple
words, the null hypothesis is accepted and the variables are
insignificant at 5% significance level.
2d: expected
score
The data for the new employee:
Relationship with supervisor = 40
Opportunities for advancement = 30
Overall quality of work environment = 75
Total hours worked per week = 60
Now, with help of the above given data and the model
presented in the summary section 2.a., the job satisfaction of
the new employee is calculated.
Job satisfaction=98.3291+1.3232∗( Relatioship withsuupervisor )−1.5224∗( Total hours wo
Job satisfaction=98.3291+1.3232∗40−1.5224∗60
¿ 59.92≃ 60
Hence, the expected job satisfaction score for the new
employee will be 60.
Question 3 answers
Can bond rate be predicted by the prime?
The bond rate can be predicted by the prime interest rate which can be
confirmed by the value of R-Squared. The value of R-squared is 0.9194. This
indicates that the model can explain 91.94% of the observed variance of the
dependent variable that is bond rate with the help of the independent variable that
is prime interest rate.
Paste scatter graph here:
The fitted regression model is presented below:
Y =3.3469∗X + 0.0457
Where, Y = Bond Rate and X = Prime Interest Rate.
The R-squared value of the model is 0.9194.

0% 2% 4% 6% 8% 10% 12% 14%
0%
10%
20%
30%
40%
50%
60%
f(x) = 3.35 x + 0.05
R² = 0.92
Scatter plot
Prime Interest Rate
Bond Rate
Figure 1: Scatter plot of Bond rate against prime interest rate