Question

Trend Analysis:

Using appropriate regression model Determine the long-term trend of the selected variable. In addition, illustrate graph of actual series and predicted trend model on same plot. Comment on long-term trend based on your findings. Report your finding as follows: Model

1 Coefficient of Intercept

2 standard error of intercept

3 Coefficient of X

4 (standard error of Coefficient of X)

5 r-square

6 t- stat of Coefficient of X

7 (P –value of Coefficient of X)

3. Cyclical Effect: Does your variable have cyclical effect? Use appropriate analysis and graph to support your answer. Present graph in word file and interpret.

Answer #1

Shown below is a portion of an Excel output for regression
analysis relating Y (dependent variable) and X (independent
variable).
ANOVA
df
SS
Regression
1
39947.80
Residual (Error)
10
8280.81
Total
11
48228.61
Coefficients
Standard Error
t Stat
P-value
Intercept
69.190
26.934
2.569
0.02795
X
2.441
0.351
6.946
0.00004
1. What is the estimated regression equation
that relates Y to X?
2. Is the regression relationship significant?
Use the p-value approach and alpha = 0.05 to answer this
question.
3. What is the...

Shown below is a
portion of an Excel output for regression analysis relating Y
(dependent variable) and X (independent variable).
ANOVA
df
SS
Regression
1
39947.80
Residual (Error)
10
8280.81
Total
11
48228.61
Coefficients
Standard
Error
t Stat
P-value
Intercept
69.190
26.934
2.569
0.02795
X
2.441
0.351
6.946
0.00004
1. What is
the estimated regression equation that relates Y to X? (2
Points)
2. Is the
regression relationship significant? Use the p-value approach and
alpha = 0.05 to answer this...

Multiple linear regression results:
Dependent Variable: Cost
Independent Variable(s): Summated Rating
Cost = -43.111788 + 1.468875 Summated Rating
Parameter estimates:
Parameter
Estimate
Std. Err.
Alternative
DF
T-Stat
P-value
Intercept
-43.111788
10.56402
≠ 0
98
-4.0810021
<0.0001
Summated Rating
1.468875
0.17012937
≠ 0
98
8.633871
<0.0001
Analysis of variance table for multiple regression model:
Source
DF
SS
MS
F-stat
P-value
Model
1
8126.7714
8126.7714
74.543729
<0.0001
Error
98
10683.979
109.02019
Total
99
18810.75
Summary of fit:
Root MSE: 10.441273
R-squared: 0.432...

Shown below is a portion of an Excel
output for regression analysis relating Y (dependent variable) and
X (independent variable).
ANOVA
df
SS
Regression
1
3348.312
Residual
8
9529.811
Total
9
12878.123
Coefficients
Standard Error
t Stat
P-value
Intercept
247.56
83.280
1.689
0.030
X
148.62
38.312
1.283
0.075
1. What is the estimated regression equation that relates y to x?
(2 Points)
2. Is the regression relationship significant? Use a p-value and
alpha = 0.05. (2 Points)
3. What is...

f. Interpret the slope coefficient for one of the dummy
variables included in your regression model.
g. For the slope coefficient of the variable with the smallest
slope coefficient (ignore sign, use absolute value), test to see if
the “a priori” expectation from part (a) is confirmed. Use alpha =
0.05.
h. Interpret the coefficient of determination in this
situation.
i. Test the explanatory power of the entire regression model.
Please use alpha = 0.01.
j. For the variable with...

Study the following Minitab output from a regression analysis to
predict y from x. a. What is the equation of the regression model?
b. What is the meaning of the coefficient of x? c. What is the
result of the test of the slope of the regression model? Let α =
.10.Why is the t ratio negative? d. Comment on r2 and the standard
error of the estimate. e. Comment on the relationship of the F
value to the t...

12.4 Study the following Minitab output from a regression analysis
to predict y from x.
a. What is the equation of the regression
model?
b. What is the meaning of the coefficient of
x?
c. What is the result of the test of the slope of
the regression model? Let α = .10.Why is the t ratio
negative?
d. Comment on r2 and the
standard error of the estimate.
e. Comment on the relationship of the F
value to the...

Use regression analysis to examine the variation in a dependent
variable. Use 0.05 level of significance unless other
stated.
When doing various tests (fit, significance) report the
relevant values of the parameters (test stats, R square)
Make sure to write out your hypotheses and rejection rules for
significance tests. If p-values are greater than 0
report the level at which your test is significant.
Conclusions are to be in terms of the problems; pretend the
reader has no idea about you were...

Question 1
How is a residual calculated in a regression model? i.e. what is
the meaning of a residual?
a)The difference between the actual value, y, and the fitted
value, y-hat
b)The difference between the fitted value, y-hat, and the mean,
y-bar
c)The difference between the actual value, y, and the mean,
y-ba
d)The square of the difference between the fitted value, y-hat,
and the mean, y-bar
Question 2
Larger values of r-squared imply that the observations are more
closely...

Statistical Analysis for Business Applications I
Consider the following data representing the total time (in hours)
a student spent on reviewing for the Stat final exam and the actual
score on the final. The sample of 10 students was taken from a
class and the following answers were reported.
time score
0 23
4 30
5 32
7 50
8 45
10 55
12 60
15 70
18 80
20 100
Part 1: Use the formulas provided on the 3rd...

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