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Questions:
Identify the continuous, binary, and categorical variables. Convert the data so that all values to be analyzed are numeric (Display a sample 10 observations in your submission).
Determine whether any of the predictor variables are significantly correlated to each other. Which independent variables are statistically significant? Evaluate the model.
Choose an offensive soccer player in a top European league (e.g., the Premier League, the La Liga, Serie A etc.) and compute his predicted market value using the regression model.
Discuss the limitations of the model and how the model can be improved. N.B.: Answers must be based on the dataset attached to the case study.
Attachment:- Case study.zip
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This assignment is predicting a players value based of past data. we use the concept of multilinear regression. we use r programming language to analyse the data. First we convert the whole data in numeric form and then find correlation between different variables. there are few variables which are correlated based on high correlation value.
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LINEAR PROGRAMMING MODELS
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