Hello Learners, In this Post, you will find NPTEL Data Science for Engineers Assignment 6 Week 6 Answers 2023. All the Answers are provided below to help the students as a reference don’t straight away look for the solutions.
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| COURSE NAME | ANSWER |
| NPTEL Data Science for Engineers Assignment 1 Answers | Click Here |
| NPTEL Data Science for Engineers Assignment 2 Answers | Click Here |
| NPTEL Data Science for Engineers Assignment 3 Answers | Click Here |
| NPTEL Data Science for Engineers Assignment 4 Answers | Click Here |
| NPTEL Data Science for Engineers Assignment 5 Answers | Click Here |
| NPTEL Data Science for Engineers Assignment 6 Answers | Click Here |
| NPTEL Data Science for Engineers Assignment 7 Answers | Click Here |
| NPTEL Data Science for Engineers Assignment 8 Answers | Click Here |
NPTEL Data Science for Engineers Assignment 6 Answers 2023:
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Q.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
Q.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
Q.3. What is the RR-Squared value of the model obtained in Q1Q1?
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Q.4. What is the adjusted RR-Squared value of the model obtained in Q1Q1?
- 0.22
- 0.7441
- 0.088
- 0.5
Q.5. Based on the model relationship obtained from Q1Q1, 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
Q.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
Q.7. If R2 is 0.6, SSR=200 and SST=500, then SSE is
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Q.8. Linear Regression is an optimization problem where we attempt to minimize
Q.9. The model built from the data given below is Y=0.2x+60. Find the values for R2 and Adjusted R
- 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
Q.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.
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About NPTEL Data Science for Engineers Course:
Learning Objectives :
- Introduce R as a programming language
- Introduce the mathematical foundations required for data science
- Introduce the first level data science algorithms
- Introduce a data analytics problem solving framework
- Introduce a practical capstone case study
Learning Outcomes:
- Describe a flow process for data science problems (Remembering)
- Classify data science problems into standard typology (Comprehension)
- Develop R codes for data science solutions (Application)
- Correlate results to the solution approach followed (Analysis)
- Assess the solution approach (Evaluation)
- Construct use cases to validate approach and identify modifications required (Creating)
Course Layout:
- Week 1: Course philosophy and introduction to R
- Week 2: Linear algebra for data science
- 1. Algebraic view – vectors, matrices, product of matrix & vector, rank, null space, solution of over-determined set of equations and pseudo-inverse)
- 2. Geometric view – vectors, distance, projections, eigenvalue decomposition
- Week 3: Statistics (descriptive statistics, notion of probability, distributions, mean, variance, covariance, covariance matrix, understanding univariate and multivariate normal distributions, introduction to hypothesis testing, confidence interval for estimates)
- Week 4: Optimization
- Week 5: 1. Optimization
- 2. Typology of data science problems and a solution framework
- Week 6: 1. Simple linear regression and verifying assumptions used in linear regression
- 2. Multivariate linear regression, model assessment, assessing importance of different variables, subset selection
- Week 7: Classification using logistic regression
- Week 8: Classification using kNN and k-means clustering
CRITERIA TO GET A CERTIFICATE:
Average assignment score = 25% of average of best 8 assignments out of the total 12 assignments given in the course.
Exam score = 75% of the proctored certification exam score out of 100
Final score = Average assignment score + Exam score
YOU WILL BE ELIGIBLE FOR A CERTIFICATE ONLY IF AVERAGE ASSIGNMENT SCORE >=10/25 AND EXAM SCORE >= 30/75. If one of the 2 criteria is not met, you will not get the certificate even if the Final score >= 40/100.
If you have not registered for exam kindly register Through https://examform.nptel.ac.in/
