RMD Lecture 6

RMD Lecture 6

1. correlation

   • start by inspecting your scatterplot
   • correlation coefficient the strength
   • non-parametric: spearman's rho

2. drawing the line

   • r=1 we can actually draw a line through the plots
   • the line is called a model
   • with high correlation, line models correlation quite well

3. regression basics: lines and predicitions

4. regression basics

   • regression line - line of best fit
   • line of best fit is the closest we can make it to all the data points
   • the variable we predict from: PREDICTOR (IV)
     • x axis
   • the variable we predict: criterion (DV)
     • y axis

5. regression lines

   • you want to predict RMD performance, could use interest hypothesis - more interest, better performance

6. regression equation

   • helps us to predict a value of Y with a given value of X
     • it has three terms (2 primary, 1 secondary)

7. y= a + b x

   • this is the formula regression
   • a = intercept: when the regression line causes the y axis
   • the slope is the bx part