# NPTEL Data Analytics with Python Assignment 1 Answers 2023

Hello NPTEL Learners, In this article, you will find NPTEL Data Analytics with Python Assignment 1 Week 1 Answers 2023. All the Answers are provided below to help the students as a reference don’t straight away look for the solutions, first try to solve the questions by yourself. If you find any difficulty, then look for the solutions.

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## NPTEL Data Analytics with Python Assignment 1 Answers 2023:

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• True
• False

#### Q.2. Which of the following is not an example of predictive analytics?

• Linear regression
• Time series analysis and forecasting
• Bar Graphs
• Data mining

• True
• False

• Height
• Year
• Age
• Weight

• print
• Input
• Write
• Msg

• 3 1 0
• 3 1 1
• 3 1 2
• 3 1 3

#### Q.7. Median is not applicable to

• Ordinal
• Interval
• Nominal
• None of the above

• True
• False

#### Q.9. Whichone of the following is not a classification of Data Analytics?

• Diagnostic analytics
• Deceptive analytics
• Predictive analytics
• Prescriptive analytics

#### Q.10.For getting 2nd, 4th & 7th row of a datafile “df”in Python programming, we can write:

• df.loc[[2,3,5]]
• df.loc[[1,3,6]]
• df.iloc[2,4,7]
• None of the above
##### NPTEL Data Analytics with Python Assignment 1 Answers Join Group👇

Disclaimer: This answer is provided by us only for discussion purpose if any answer will be getting wrong don’t blame us. If any doubt or suggestions regarding any question kindly comment. The solution is provided by Chase2learn. This tutorial is only for Discussion and Learning purpose.

#### About NPTEL Data Analytics with Python Course:

We are looking forward to sharing many exciting stories and examples of analytics with all of you using python programming language. This course includes examples of analytics in a wide variety of industries, and we hope that students will learn how you can use analytics in their career and life. One of the most important aspects of this course is that you, the student, are getting hands-on experience creating analytics models; we, the course team, urge you to participate in the discussion forums and to use all the tools available to you while you are in the course!

##### Course Outcome:
• Week 1 : Introduction to data analytics and Python fundamentals
• Week 2 : Introduction to probability
• Week 3 : Sampling and sampling distributions
• Week 4 : Hypothesis testing
• Week 5 : Two sample testing and introduction to ANOVA
• Week 6 : Two way ANOVA and linear regression
• Week 7 : Linear regression and multiple regression
• Week 8 : Concepts of MLE and Logistic regression
• Week 9 : ROC and Regression Analysis Model Building
• Week 10 : c2 Test and introduction to cluster analysis
• Week 11 : Clustering analysis
• Week 12 : Classification and Regression Trees (CART)
###### 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.

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