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Advanced Statistics

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Dear Participants,

Please refer to the Project video for complete context about the “Advance Statistics” problem.

The objective of the project is to use the dataset ‘Factor-Hair-Revised.csvView in a new window’ to build an optimum regression model to predict satisfaction. You are expected to

Perform exploratory data analysis on the dataset. Showcase some charts, graphs. Check for outliers and missing values (8 marks)

Is there evidence of multicollinearity ? Showcase your analysis(6 marks)

Perform simple linear regression for the dependent variable with every independent variable (6 marks)

Perform PCA/Factor analysis by extracting 4 factors. Interpret the output and name the Factors (20 marks)

Perform Multiple linear regression with customer satisfaction as dependent variables and the four factors as independent variables. Comment on the Model output and validity. Your remarks should make it meaningful for everybody

(20 marks)

Please note the following:

Your submission should be a Word Document or PDF.

You must give the sources of data presented. Do not refer to blogs; Wikipedia etc.

Any assignment found copied/ plagiarized with other group(s) will not be graded and marked as zero.

Please ensure timely submission as post deadline assignment will not be accepted.

Advanced Statistics was first posted on August 24, 2019 at 5:36 pm.
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