MGT 6203 FINAL EXAM QUESTIONS AND ANSWERS Exam (elaborations)
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Course
MGT 6203
Institution
Georgia Institute Of Technology
MGT 6203 /MGT 6203 FINAL EXAM QUESTIONS AND ANSWERS.Theory - 20 questions Week 1 Questions Q1. If the explained sum of squares is 35 and the total sum of squares is 49, what is the residual sum of squares? A. 10 B. 14 C. 12 D. 18 Solution: B Explanation: Total Sum of Squares = Explained Sum of Squa...
mgt 6203 final exam questions and answers exam elaborations
mgt 6203 final exam questions and answers
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MGT 6203
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MGT 6203 FINAL EXAM QUESTIONS AND ANSWERS
Exam (elaborations)
, FINAL EXAM QUESTIONS
2020
Theory - 20 questions
Week 1 Questions
Q1. If the explained sum of squares is 35 and the total sum of squares is 49, what is the
residual sum of squares?
A. 10
B. 14
C. 12
D. 18
Solution: B
Explanation: Total Sum of Squares = Explained Sum of Squares + Residual Sum of Squares
SST = SSE + SSR
SSR = SST – SSE = 49 – 35 = 14
Week 2 Questions
Q2. Consider a regression model predicting the amount someone has spent (on some
arbitrary product) based on their salary and age. To improve the model we have created an
interaction variable between Salary and Age. Assume salary given in dollars, and age in
years.
b0 = 500
b1 = 0.35
b2 = 0.12
b3=0.21
AmountSpent = b0 + b1Salary + b2Age + b3SalaryAge
How much more will a 30-year old person with a salary of $20,000 spend than a person who
is 2 years older and earns $5000 less than him/her?
a)17500
b)33249.54
c)26949.76
d)26950.24
, Q3 Given the independent variable X and dependent variable Y, we regress Y on log(X)
and get the following formula: Y = b1 * log(X) + b0 where b1 and b0
are the estimated coefficient and intercept respectively
from OLS regression. How should we interpret it?
A. As X increases by 1 unit, Y increases by b1 units
B. As X increases by 1%, Y increases by 0.01 b1 units
C. As X increases by 1 unit, Y increases by 100( e b −1 )%
1
D. As X increases by 1%, Y increases by 100( e 0.01 b −1 )%
1
Answer: B
As X increases by 1%, log(X) becomes log(X) + 0.01 and y_new = b1 *(log(X) + 0.01) +
b0 = y_old + 0.01 b1
Refer to Week 3 TA session notes
Week 4 Questions
Q4 Select the option from below which is TRUE regarding the False Positive Rate:
A). A model with high Specificity will have a high False Positive Rate.
B). A model with high Specificity will have a low False Positive Rate.
C). The False Positive Rate of a model is not dependent on the number of
True Negatives
D). The False Positive Rate is given by the formula: False Positive / (True Negatives
+ True Positives)
Answer: Option B.
Week 5 Questions
Q5 What is the orthogonality assumption in OLS, taking Y = a + bX as the model, and error
term is e?
(A) Correlation(X, X) = 0
(B) Correlation(X, e) = 0
(C) Correlation(e, X) = 1
(D) None of the above
Ans: (B)
The orthogonality assumption in OLS is that the error terms and predictors are not related
at all.
(Week 5, Lesson 2)
Week 7 Questions
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