Nptel Data Science for Engineers Assignment 6 Answers
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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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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
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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
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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
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
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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)
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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
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These are Data Science for Engineers Week 6 Answers
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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
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
