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The objective of the project is to use the dataset 'Factor-Hair-Revised.csv' 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
· Is there evidence of multicollinearity? Showcase your analysis
· Perform simple linear regression for the dependent variable with every independent variable
· Perform PCA/Factor analysis by extracting 4 factors. Interpret the output and name the Factors
· 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
Note: the calculations should be performed using R code. and should be provided in the report.
Operations Management is about a book review. Title of the book is "Goal". This book has been written by Dr. Eliyahu Goldartt. The book has been appreciated by many as one of those books which offers an insight into the operations and strategic capac..
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An analysis of the holding costs, including the appropriate annual holding cost rate.
Briefly explain Evolution and contributor of Operations management.
A number of drivers of change have transformed the roles, functions and responsibilities of an operations manager over recent years. These drivers have not only been based on technological innovations but also on the need for organisations to develop..
Compute the Optimal Order quantity of DVD players. Determine the appropriate reorder point.
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Develop a report for Figi Fabricating that will address the question of whether the company should continue to purchase the part from the supplier or begin to produce the part itself.
Prepare a staffing plan showing the change of your unit from medical/surgical staffing to oncology staffing.
Ccompare the effectiveness of different leadership styles in different organizations
Be able to understand the concept of risk, roles and responsibilities for risk management and risk management tools and models.
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