# Nptel Data Science for Engineers Assignment 6 Answers

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## Table of Contents

**Nptel Data Science for Engineers Assignment 6 Answers (July-Dec 2024)**

**1. What is the relationship between the variables, Coupon rate and Bid price?**

A) Coupon rate = 99.95 + 0.24 * Bid price

B) Bid price = 99.95 + 0.24 * Coupon rate

C) Bid price = 74.7865 + 3.066 * Coupon rate

D) Coupon rate = 74.7865 + 3.066 * Bid price

**Answer:** C) Bid price = 74.7865 + 3.066 * Coupon rate

**2. Choose the correct option that best describes the relation between the variables Coupon rate and Bid price in the given data.**

A) Strong positive correlation

B) Weak positive correlation

C) Strong negative correlation

D) Weak negative correlation

**Answer:** A) Strong positive correlation

**3. What is the R-Squared value of the model obtained in Q1?**

A) 0.2413

B) 0.12

C) 0.7516

D) 0.5

**Answer:** C) 0.7516

**4. What is the adjusted R-Squared value of the model obtained in Q1?**

A) 0.22

B) 0.7441

C) 0.088

D) 0.5

**Answer:** B) 0.7441

**5. Based on the model relationship obtained from Q1, what is the residual error obtained while calculating the bid price of a bond with a coupon rate of 3?**

A) 10.5155

B) -10.5155

C) 6.17

D) 0

**Answer:** D) 0

**6. State whether the following statement is True or False. Covariance is a better metric to analyze the association between two numerical variables than correlation.**

A) True

B) False

**Answer:** B) False

**7. If ( R^2 ) is 0.6, SSR=200, and SST=500, then SSE is:**

A) 500

B) 200

C) 300

D) None of the above

**Answer:** C) 300

**8. Linear Regression is an optimization problem where we attempt to minimize:**

A) SSR (residual sum-of-squares)

B) SST (total sum-of-squares)

C) SSE (sum-squared error)

D) Slope

**Answer:** C) SSE (sum-squared error)

**9. The model built from the data given below is ( Y = 0.2x + 60 ). Find the values for ( R^2 ) and Adjusted ( R^2 ).**

A) ( R^2 ) is 0.022 and Adjusted ( R^2 ) is −0.303

B) ( R^2 ) is 0.022 and Adjusted ( R^2 ) is −0.0303

C) ( R^2 ) is 0.022 and Adjusted ( R^2 ) is 0.303

D) None of the above

**Answer:** D) None of the above

**10. Identify the parameters ( \beta_0 ) and ( \beta_1 ) that fit the linear model ( \beta_0 + \beta_1 x ) using the following information: total sum of squares of X, ( SS_{XX} = 52.53 ), ( SS_{XY} = 52.01 ), mean of X, ( \bar{X} = 4.46 ), and mean of Y, ( \hat{Y} = 6.32 ).**

A) 1.9 and 0.99

B) 10.74 and 1.01

C) 4.42 and 1.01

D) None of the above

**Answer:** A) 1.9 and 0.99

** These are Data Science for Engineers Nptel Assignment Solutions Week **6

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**Nptel Data Science for Engineers Assignment 6 Answers (JAN-APR 2024**)

**Course Name: Data Science for Engineers**

**Course Link: Click Here**

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**These are Data Science for Engineers Week 6 Answers**

**Q1. What is the relationship between the variables, Coupon rate and Bid price?**

Coupon rate = 99.95 + 0.24 * Bid price

Bid price = 99.95 + 0.24 * Coupon rate

Bid price = 74.7865 + 3.066 * Coupon rate

Coupon rate = 74.7865 + 3.066 * Bid price

**Answer: Bid price = 74.7865 + 3.066 * Coupon rate**

**Q2. Choose the correct option that best describes the relation between the variables Coupon rate and Bid price in the given data.**

Strong positive correlation

Weak positive correlation

Strong negative correlation

Weak negative correlation

**Answer: Strong positive correlation**

**For answers or latest updates join our telegram channel: Click here to join**

**These are Data Science for Engineers Week 6 Answers**

**Q3. What is the R-Squared value of the model obtained in Q1?**

0.2413

0.12

0.7516

0.5

**Answer: 0.7516**

**Q4. What is the adjusted R-Squared value of the model obtained in Q1?**

0.22

0.7441

0.088

0.5

**Answer: 0.7441**

**For answers or latest updates join our telegram channel: Click here to join**

**These are Data Science for Engineers Week 6 Answers**

**Q5. Based on the model relationship obtained from Q1, what is the residual error obtained while calculating the bid price of a bond with coupon rate of 3?**

10.5155

-10.5155

6.17

0

**Answer: 10.5155**

**Q6. State whether the following statement is True or False.Covariance is a better metric to analyze the association between two numerical variables than correlation.**

True

False

**Answer: False**

**For answers or latest updates join our telegram channel: Click here to join**

**These are Data Science for Engineers Week 6 Answers**

**Q7. If R2 is 0.6, SSR=200 and SST=500, then SSE is**

500

200

300

None of the above

**Answer: 300**

**Q8. Linear Regression is an optimization problem where we attempt to minimize**

SSR (residual sum-of-squares)

SST (total sum-of-squares)

SSE (sum-squared error)

Slope

**Answer: SSE (sum-squared error)**

**For answers or latest updates join our telegram channel: Click here to join**

**These are Data Science for Engineers Week 6 Answers**

**Q9. The model built from the data given below is Y = 0.2x + 60. Find the values for R2 and Adjusted R2**

R2 is 0.022 and Adjusted R2 is −0.303

R2 is 0.022 and Adjusted R2 is −0.0303

R2 is 0.022 and Adjusted R2 is 0.303

None of the above

**Answer: R2 is 0.022 and Adjusted R2 is −0.303**

**Q10. Identify the parameters β0 and β1 that fits the linear model β0+β1x using the following information: total sum of squares of X,SSXX=52.53,SSXY=52.01, mean of X,X¯=4.46, and mean of Y,Y^=6.32.**

1.9 and 0.99

10.74 and 1.01

4.42 and 1.01

None of the above

**Answer: 1.9 and 0.99**

**For answers or latest updates join our telegram channel: Click here to join**

**These are Data Science for Engineers Week 6 Answers**

More Solutions of Data Science for Engineers: Click Here

More Nptel Courses: Click here

**Nptel Data Science for Engineers Assignment 6 Answers (JULY-DEC 2023)**

**Course Name: Data Science for Engineers**

**Course Link: Click Here**

**These are Data Science for Engineers Week 6 Answers**

**Q1. What is the relationship between the variables, Coupon rate and Bid price?**

Coupon rate = 99.95 + 0.24 * Bid price

Bid price = 99.95 + 0.24 * Coupon rate

Bid price = 74.7865 + 3.066 * Coupon rate

Coupon rate = 74.7865 + 3.066 * Bid price

**Answer: Bid price = 74.7865 + 3.066 * Coupon rate**

**Q2. Choose the correct option that best describes the relation between the variables Coupon rate and Bid price in the given data.**

Strong positive correlation

Weak positive correlation

Strong negative correlation

Weak negative correlation

**Answer: Strong positive correlation**

**These are Data Science for Engineers Week 6 Answers**

**Q3. What is the R-Squared value of the model obtained in Q1?**

0.2413

0.12

0.7516

0.5

**Answer: 0.7516**

**Q4. What is the adjusted R-Squared value of the model obtained in Q1?**

0.22

0.7441

0.088

0.5

**Answer: 0.7441**

**These are Data Science for Engineers Week 6 Answers**

**Q5. Based on the model relationship obtained from Q1, what is the residual error obtained while calculating the bid price of a bond with coupon rate of 3?**

10.5155

-10.5155

6.17

0

**Answer: 10.5155**

**Q6. State whether the following statement is True or False.Covariance is a better metric to analyze the association between two numerical variables than correlation.**

True

False

**Answer: False**

**These are Data Science for Engineers Week 6 Answers**

**Q7. If R2 is 0.6, SSR=200 and SST=500, then SSE is**

500

200

300

None of the above

**Answer: 300**

**Q8. Linear Regression is an optimization problem where we attempt to minimize**

SSR (residual sum-of-squares)

SST (total sum-of-squares)

SSE (sum-squared error)

Slope

**Answer: SSE (sum-squared error)**

**These are Data Science for Engineers Week 6 Answers**

**Q9. The model built from the data given below is Y=0.2x+60. Find the values for R2 and Adjusted R2.**

R2 is 0.022 and Adjusted R2 is −0.303

R2 is 0.022 and Adjusted R2 is −0.0303

R2 is 0.022 and Adjusted R2 is 0.303

None of the above

**Answer: R2 is 0.022 and Adjusted R2 is −0.303**

**Q10. Identify the parameters β0 and β1 that fits the linear model β0+β1x using the following information: total sum of squares of X,SSXX=52.53,SSXY=52.01, mean of X,X¯=4.46, and mean of Y,Y^=6.32.**

1.9 and 0.99

10.74 and 1.01

4.42 and 1.01

None of the above

**Answer: 1.9 and 0.99**