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✅ Subject: Nptel Data Science for Engineers
📅 Week: 6
🎯 Session: NPTEL 2025
🔗 Course Link: Data Science for Engineers
🔍 Reliability: Verified and expert-reviewed answers
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NPTEL Data Science for Engineers Week 6 Assignment Answers 2025
1. 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 :- For Answers Click Here
2. 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 :-
3. What is the R-Squared value of the model obtained in Q1?
- 0.2413
- 0.12
- 0.7516
- 0.5
Answer :- For Answers Click Here
Introduction To Internet Of Things Week 6 NPTEL Assignment Answers 2025
4. What is the adjusted R-Squared value of the model obtained in Q1?
- 0.22
- 0.7441
- 0.088
- 0.5
Answer :-
5. 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 :-
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.
- True
- False
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7. If R2 is 0.6, SSR=200 and SST=500, then SSE is
- 500
- 200
- 300
- None of the above
Answer :-
8. 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 :-
9 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 −0.303
- R2 is 0.022 and Adjusted R2 is 0.303
- None of the above
Answer :-
10. 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 :- For Answers Click Here
Data Science for Engineers Week 6 NPTEL Assignment Answers 2024
1. 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 :- c
2. 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 :- a
3. What is the R-Squared value of the model obtained in Q1?
- 0.2413
- 0.12
- 0.7516
- 0.5
Answer :- c
4. What is the adjusted R-Squared value of the model obtained in Q1?
- 0.22
- 0.7441
- 0.088
- 0.5
Answer :- b
5. 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 :- a
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.
- True
- False
Answer :- b
7. If R2 is 0.6, SSR=200 and SST=500, then SSE is
- 500
- 200
- 300
- None of the above
Answer :- c
8. 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 :- c
9. 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 :- a
10. Identify the parameters β0 and β1 that fits the linear model β0 + β1 x 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 :- a
Conclusion:
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