NPTEL Data Science for Engineers Week 6 Assignment 2025

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NPTEL Data Science for Engineers Week 6 Assignment 2025

NPTEL Data Science for Engineers Week 6 Assignment 2025


In this Week 6, the following topics are discussed:

  • Predictive Modelling
  • Linear Regression
  • Simple Linear Regression
Last Date: 05-03-2025

For the following set of questions 1, 2, 3, 4, 5, use the dataset bonds.txt. This dataset contains 2 variables, Coupon rate and Bid price.

Q1. 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

Q2. 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

Q3. 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

Q4. 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

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?

 A. 10.5155

 B. -10.5155

 C. 6.17

 D. 0

Answer: [ A ] 10.5155

State whether the following statement is True or False.

Q6. Covariance is a better metric to analyze the association between two numerical variables than correlation.

 A. True

 B. False

Answer: [ B ] False

Q7. 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

Q8. 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)

Q9. The model built from the data given below is Y=0.2x+60. Find the values for R^2 and Adjusted R^2.

A. R2 is 0.022 and Adjusted R2 is −0.303

B. R2 is 0.022 and Adjusted R2 is −0.303

C. R2 is 0.022 and Adjusted R2 is 0.303

D. None of the above

Answer: [ D ] None of the Above

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.

 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

Conclusion

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