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MGT 6203 Graded Homework 2_ Data Analytics Business | Graded A+

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Ques 5 / 5 pts tion 1 In a linear regression problem, we are using “R-squared” to measure goodness-of-fit. We add a feature (variable) in linear regression model and retrain the same model. Which of the following option is true? If R Squared increases, this variable is significant. If R Squared decreases, this variable is not significant. Individually R squared cannot tell about variable importance. We can’t say anything about it right now. None of these. Ques 0 / 5 pts tion 2 Incorrect A correlation between age and health of a person found to be -1.09. On the basis of this, you would tell the doctors that: Age is a good predictor of health Health is a good predictor of age Age is a poor predictor of health None of these Ques 5 / 5 pts tion 3 You work for a bank where you are trying to predict the probability of default of a customer based on FICO score and annual income. Which of the following problems can arise while using a multiple linear regression model? There exists homoskedasticity in the model. The model can produce predicted probabilities that are less than zero and greater than one. The model leads to the omitted variable bias as only two independent factors can be included in the model. The model leads to an overestimation of the effect of independent variables on the dependent variable. We try to build a model for NBA players’ salary. Download the dataset from here: ( ( Load the dataset using the code nba = ("", header = TRUE). Now we take a closer look at the data set. There are four variables salary, Ht(Height), Exp(Experience) and expsq(the square of Experience). First, build a model using salary as the response and Ht and Exp as variables and denote it as Model_1. Build a second model using log(salary) as the response and Ht and Exp as variables, we denote it as Model_2. 4/14/2020 Graded Homework #2: Data Analytics Business - MGT-6203-OAN Ques 5 / 5 pts tion 4 For Model_1, what is the interpretation for the coefficient of height?

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4/14/2020 Graded Homework #2: Data Analytics Business - MGT-6203-OAN


 This quiz has been regraded; your new score reflects 2 questions that were affected.


Graded Homework #2
Due Feb 26 at 11:59pm Points 100 Questions 20
Available Feb 7 at 8am - Feb 26 at 11:59pm 20 days Time Limit None


Instructions
Graded Homework #2 covers the topics in Weeks 1, 2, 3, 4 ,5 and 6 and is worth 10% of your overall
grade. You may work on the homework for as long as you like within the given window. You are allowed
only ONE attempt for submission. Please note that your answers will automatically save as you key
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This quiz was locked Feb 26 at 11:59pm.



Attempt History
Attempt Time Score Regraded
LATEST Attempt 1 1,794 minutes 75 out of 100 80 out of 100




 Correct answers are hidden.

Score for this quiz: 80 out of 100
Submitted Feb 21 at 10:28am
This attempt took 1,794 minutes.


Question 1 pts


In a linear regression problem, we are using “R-squared” to measure
goodness-of-fit. We add a feature (variable) in linear regression model
and retrain the same model.

https://gatech.instructure.com/courses/94184/quizzes/99397?module_item_id=558150 1/13

, 4/14/2020 Graded Homework #2: Data Analytics Business - MGT-6203-OAN




Which of the following option is true?


If R Squared increases, this variable is significant.


If R Squared decreases, this variable is not significant.



Individually R squared cannot tell about variable importance. We can’t say
anything about it right now.



None of these.




Incorrect
Question 2 pts


A correlation between age and health of a person found to be -1.09. On
the basis of this, you would tell the doctors that:


Age is a good predictor of health


Health is a good predictor of age


Age is a poor predictor of health


None of these




Question 3 pts


You work for a bank where you are trying to predict the probability of
default of a customer based on FICO score and annual income. Which of



https://gatech.instructure.com/courses/94184/quizzes/99397?module_item_id=558150 2/13

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