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3.3

Regression Analysis

QuestionAnswer
Regression determines the relationship between two data sets
Goodness of fit is defined by R-squared How much of the dependent variable can be determined by the independent variable?
The p-value of your regression analysis comes out to be 0.62. Is the independent variable a significant predictor of the dependent variable? Can we reject the null? No. LESS than 0.05 means Yes. 0.62 is higher than 0.05. No significance.
The R-squared value is 0.71. Is this a strong goodness of fit? Yes. On a scale of 0% - 100%, 71% is a strong fit. 71% of the dependent is made up from the independent.
We wish to determine if the minutes student spend taking a test can predict their test score. In this scenario, which is the independent variable? Minutes spend taking the test.
As a new manager, you analyze the number of clicks into your website each subscriber makes in a month to determine how much they spend. In this scenario, spending is which variable? Dependent. The dependent is always what we are trying to predict.
Can correlation be a negative number? Yes.
True or False: -0.99 is a stronger relationship than 0.74 True
Linear regression is often referred to as Ordinary Least Squares (OLS) Regression
y = 10x + 50. Solve for y if x = 10 y = 10(10) + 50 y = 150
Our regression module for number of clicks predicting spending on our website is y = 6 + 5x. If a subscriber has 4 clicks, how much will they spend? y = 6 + 5(4) y = 26
Created by: mgallo3
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