Data Science & Big Data
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Get it written →ISLR An Introduction to Statistical Learning, Gareth James, Daniela Witten, Trevor Hastie and Robert Tibshirani,
3 Linear Regression 59
3.1 Simple Linear Regression . . . . . . . . . . . . . . . . . . . 61
3.1.1 Estimating the Coefficients . . . . . . . . . . . . . . 61
3.1.2 Assessing the Accuracy of the Coefficient Estimates . . . . . . . . . . . . . . . . . . . . . . . . 63
3.1.3 Assessing the Accuracy of the Model . . . . . . . . . 68
3.2 Multiple Linear Regression . . . . . . . . . . . . . . . . . . 71
3.2.1 Estimating the Regression Coefficients . . . . . . . . 72
3.2.2 Some Important Questions . . . . . . . . . . . . . . 75
3.3 Other Considerations in the Regression Model . . . . . . . . 82
3.3.1 Qualitative Predictors . . . . . . . . . . . . . . . . . 82
3.3.2 Extensions of the Linear Model . . . . . . . . . . . . 86
3.3.3 Potential Problems . . . . . . . . . . . . . . . . . . . 92
3.4 The Marketing Plan . . . . . . . . . . . . . . . . . . . . . . 102
3.5 Comparison of Linear Regression with K-Nearest Neighbors . . . . . . . . . . . . . . . . . . . . . . . . . . . . 104
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