Bivariate+Data

**1.(this page) Linear Regression**

 * 2. Linear Regression: Linear Regression 1**


 * 2.Link:** **Transformations to Achieve Linearity**

**3. Link: Test of Association -** **Spearman's Rank Order Correlation**
media type="custom" key="5200581" __Exploring a Linear Regression Model Using JMP TUTORIAL__ Linear Regression Considerations:
 * 1) Determine if a linear model is a good fit looking at:
 * Correlation coefficient (r)
 * Residual plot
 * Coefficient of determination (r-squared)
 * Least Squares Line
 * Density Ellipse
 * 1) Interpret slope and y-intercept
 * 2) Explore potential of influential or outliers
 * 3) Use the line of best fit to predict values
 * 4) Even if one variable is potentially useful to predict another, can we imply correlation -> causation?