Question

1) If an interaction term is significant, one should attempt to interpret the significance of main parameter effects by themselves/in isolation.

True or False

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2) If you observe high levels of correlation between interaction terms and main parameter effects, what should you do?

a) Remove the interaction terms.

b) Include more interaction terms.

c) Test for non-normality and sources of residual error.

d) Remove some of the main parameters.

e) Nothing - high levels of correlation between interaction terms and main effects are expected.

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3) What conclusion can we reach if a dummy variable is significant?

a) We accept the null hypothesis and conclude that the variable does not add to the model's explanatory power.

b) We reject the null hypothesis and conclude that the variable does not add to the model's explanatory power.

c) We reject the null hypothesis and conclude that the variable does add to the model's explanatory power.

d) We accept the null hypothesis and conclude that the variable does add to the model's explanatory power.

e) None of the above

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4) What happens to standard error of coefficients in a linear regression model if we increase the sample size (no. of data points) keeping the structure of the model and the predictors same?

a) Decreases

b) Increases

c) Remains the same

d) Need more information

Answer #1

1.If an interaction term is significant, one should attempt to interpret the significance of main parameter effects by themselves/in isolation

ans-> False

2. If you observe high levels of correlation between interaction terms and main parameter effects, what should you do

ans-> a) Remove the interaction terms.

3. The conclusion that we can reach if a dummy variable is significant

c) We reject the null hypothesis and conclude that the variable does add to the model's explanatory power.

4. The standard error of coefficients in a linear regression model if we increase the sample size (no. of data points) keeping the structure of the model and the predictors same

ans-> a) Decreases

A two-way analysis of variance experiment with no interaction is
conducted. Factor A has three levels (columns) and Factor
B has seven levels (rows). The results include the
following sum of squares terms:
SST = 346.9 SSA = 196.3 SSE =
79.0
a. Construct an ANOVA table. (Round
intermediate calculations to at least 4 decimal places. Round
"SS" to 2 decimal places, "MS" to 4 decimal
places, "F" to 3 decimal places.)
Source
SS
df
MS
F
p-value
Rows
Columns...

Problem 4. Once again you will be
using the EXPRESS data set. The first 10 observations are given for
illustrative purposes.
Weight
Distance
Cost
5.9
47
2.6
3.2
145
3.9
4.4
202
8
6.6
160
9.2
0.75
280
4.4
0.7
80
1.5
6.5
240
14.5
4.5
53
1.9
0.6
100
1
7.5
190
14
a) Write out a complete general first-order
model including an interaction term for Cost as the outcome.
b) Using Minitab, fit a model including the interaction...

1, Which one of the following equations contains the true error
term? Pick 1
Y-hat = α+ β X
None of the above
Y-hat = a+ b X
Y = α+ β X + ε
All of the above
Y = a+ b X + e
2,
After running a regression, we calculate the coefficient of
determination r2 = 0.94. How to interpret this
r2? Pick 1
The variation of Y is 94%.
94% of variation in Y is explained by...

Use the following linear regression equation to answer the
questions.
x1 = 1.1 + 3.0x2 –
8.4x3 + 2.3x4
(a) Which variable is the response variable?
x3
x1
x2
x4
Which variables are the explanatory variables? (Select all that
apply.)
x1
x2
x3
x4
(b) Which number is the constant term? List the coefficients with
their corresponding explanatory variables.
constant =
x2 coefficient=
x3 coefficient=
x4 coefficient=
(c) If x2 = 4, x3 = 10, and
x4 = 6, what...

1) Which is NOT a fundamental assumption of OLS (Ordinary Least
Squares)?
a) The regression model is nonlinear
in the coefficients and error term.
b) Observations of the
error term are uncorrelated with each other.
c) No independent variable is a
perfect linear function of any other explanatory variables.
d) The error term has
homoscedasticity.
e) All independent variables will be uncorrelated
with the error term.
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2) You test a model that...

Use the following linear regression equation to answer the
questions.
x1 = 1.5 + 3.5x2 –
8.2x3 + 2.1x4
(a) Which variable is the response variable?
A. x3
B.
x1
C. x2
D. x4
(b) Which variables are the explanatory variables?
(Select all that apply.)
A. x4
B. x1
C. x3
D. x2
(c) Which number is the constant term? List the
coefficients with their corresponding explanatory variables.
constant ____________
x2 coefficient_________
x3 coefficient_________
x4 coefficient_________
(d) If x2 =...

Chapter 13
A Factorial ANOVA was conducted on the data set
“Goggles.sav” in the Field textbook. Results are
below:
Tests of Between-Subjects Effects
Dependent Variable: Attractiveness of Date
Source
Type III Sum of Squares
Df
Mean Square
F
Sig.
Corrected Model
5479.167a
5
1095.833
13.197
.000
Intercept
163333.333
1
163333.333
1967.025
.000
Sex
168.750
1
168.750
2.032
.161
Alcohol
3332.292
2
1666.146
20.065
.000
Sex * Alcohol
1978.125
2
989.062
11.911
.000
Error
3487.500
42
83.036
Total
172300.000
48
Corrected...

1. A hypothesis test is conducted with a significance level of
5%. The alternative hypothesis states that more than 65% of a
population is right-handed. The p-value for the test is calculated
to be 0.03. Which of the following statements is correct?
A .We can conclude that more than 3% of the population is
right-handed.
B .We cannot conclude that more than 65% of the population is
right-handed.
C .We can conclude that more than 65% of the population is...

QUESTION 1
For a combination of α (level of significance) = 0.05, n (sample
size) = 25, k (number of independent variables in the model) = 1
and D (Durbin-Watson statistic) = 3.30 , what statistical decision
should be made when testing the null hypothesis of no negative
autocorrelation?
a.
Neither reject nor not reject the null hypothesis.
b.
Do not reject the null hypothesis.
c.
Accept the null hypothesis.
d.
Reject the null hypothesis
1 points
QUESTION 2...

need step by step for MINITAB please
Problem 1. Consider the GASTURBINE data set and corresponding
output from Minitab. Use the complete data set in your analysis.
The first 10 observations are given for illustrative purposes.
Complete parts a) through g) below.
ENGINE
SHAFTS
RPM
CPRATIO
INLET-TEMP
EXH-TEMP
AIRFLOW
POWER
HEATRATE
Traditional
1
27245
9.2
1134
602
7
1630
14622
Traditional
1
14000
12.2
950
446
15
2726
13196
Traditional
1
17384
14.8
1149
537
20
5247
11948
Traditional
1...

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