Note: Solve all the above questions using Python. Use Pandas, Seaborn, Sklearn, etc. libraries for all...
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Note: Solve all the above questions using Python. Use Pandas, Seaborn, Sklearn, etc. libraries for all the following analysis. Consider data given in file HW5DataA ¹. Consider the following data description: Field Gender Table 1: Data Description Description Gender of the student Location Home City of the student Quiz-1 Quiz-2 Quiz-3 Quiz-4 Major-1 Major-2 Major-3 Score of the student in Quiz-1 Score of the student in Quiz-2 Score of the student in Quiz-3 Score of the student in Quiz-4 Score of the student in Major-1 Score of the student in Major-2 Score of the student in Major-3 Final Score of the student in the final exam. Gender Male Female Female Male Female Female Male Female Male Male Male Male Male Female Male Female Female Female Female Female Female Male Male Female Female Male Female Female Female Female Female Female Male Male Male Female Quiz-1 + 17 10 7 22 21 14 21 16 20 15 13 9 10 14 2 16 15 18 8 15 17 18 12 15 20 1 9 13 9 10 20 19 LO 00 Quiz-2 17 21 21 10 15 24 2 13 23 20 13 12 17 22 8 7 16 5 5 9 SE 8 18 14 13 20 13 10 17 11 24 FER Quiz- 24 14 23 21 17 5 21 6 5 11 5 19 14 13 20 14 15 21 15 14 14 5 14 9 10 19 11 22 7 21 23 Quiz-4 16 8 12 18 14 21 25 12 21 11 10 11 10 18 196 20 8 8 19 17 11 9 12 13 0 4 9 6 6 21 18 980 Major- 100 16 62 52 19 28 87 94 46 39 83 61 41 41 79 47 31 34 57 46 Major-2 30 27 62 26 Major-3 78 88 88 95 58 82 64 62 18 46 90 28 42 63 84 33 42 95 62 44 50 74 31 18 32 52 31 29 76 62 71 85 33 36 84 18 85 43 37 81 69 40 46 FERR 52 29 21 82 B-5: Correlation Analysis. Do the following: • Calculate the correlation between all the score columns of HW5DataA. • Identify top 3 variables that are highly correlated with 'Final' score column. • Which pair of score columns are strongly correlated? Note: Solve all the above questions using Python. Use Pandas, Seaborn, Sklearn, etc. libraries for all the following analysis. Consider data given in file HW5DataA ¹. Consider the following data description: Field Gender Table 1: Data Description Description Gender of the student Location Home City of the student Quiz-1 Quiz-2 Quiz-3 Quiz-4 Major-1 Major-2 Major-3 Score of the student in Quiz-1 Score of the student in Quiz-2 Score of the student in Quiz-3 Score of the student in Quiz-4 Score of the student in Major-1 Score of the student in Major-2 Score of the student in Major-3 Final Score of the student in the final exam. Gender Male Female Female Male Female Female Male Female Male Male Male Male Male Female Male Female Female Female Female Female Female Male Male Female Female Male Female Female Female Female Female Female Male Male Male Female Quiz-1 + 17 10 7 22 21 14 21 16 20 15 13 9 10 14 2 16 15 18 8 15 17 18 12 15 20 1 9 13 9 10 20 19 LO 00 Quiz-2 17 21 21 10 15 24 2 13 23 20 13 12 17 22 8 7 16 5 5 9 SE 8 18 14 13 20 13 10 17 11 24 FER Quiz- 24 14 23 21 17 5 21 6 5 11 5 19 14 13 20 14 15 21 15 14 14 5 14 9 10 19 11 22 7 21 23 Quiz-4 16 8 12 18 14 21 25 12 21 11 10 11 10 18 196 20 8 8 19 17 11 9 12 13 0 4 9 6 6 21 18 980 Major- 100 16 62 52 19 28 87 94 46 39 83 61 41 41 79 47 31 34 57 46 Major-2 30 27 62 26 Major-3 78 88 88 95 58 82 64 62 18 46 90 28 42 63 84 33 42 95 62 44 50 74 31 18 32 52 31 29 76 62 71 85 33 36 84 18 85 43 37 81 69 40 46 FERR 52 29 21 82 B-5: Correlation Analysis. Do the following: • Calculate the correlation between all the score columns of HW5DataA. • Identify top 3 variables that are highly correlated with 'Final' score column. • Which pair of score columns are strongly correlated?
Expert Answer:
Answer rating: 100% (QA)
First lets import the necessary libraries and load the data into a Pandas DataFrame import pandas as pd import seaborn as sns import matplotlibpyplot as plt from sklearnlinearmodel import LinearRegres... View the full answer
Related Book For
Applied Regression Analysis and Other Multivariable Methods
ISBN: 978-1285051086
5th edition
Authors: David G. Kleinbaum, Lawrence L. Kupper, Azhar Nizam, Eli S. Rosenberg
Posted Date:
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