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Multiple Linear Regression

In this lesson, you will be extending your knowledge of simple linear regression, where you were predicting a quantitative response variable using a quantitative explanatory variable. That is, you were using an equation that looked like this: \hat{y} = b_0 + b_1x_1y^​=b0​+b1​x1​ In this lesson, you will learn about multiple linear regression. In these cases, …

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Logistic Regression

Fitting Logistic Regression import numpy as np import pandas as pd import statsmodels.api as sm df = pd.read_csv(‘./fraud_dataset.csv’) df.head() 1. As you can see, there are two columns that need to be changed to dummy variables. Replace each of the current columns to the dummy version. Use the 1 for weekday and True, and 0 otherwise. Use the first …