STATS 10 Lecture Notes - Lecture 5: Dependent And Independent Variables, Scatter Plot
Document Summary
Correlation says there seems to be a linear association between these two variables but it doesn"t tell us what that association is. We can say more about the linear relationship between two quantitative variables with a model. A model simplifies reality to help us understand underlying patterns and relationships. The linear model is just an equation of a straight line through the data. The points in the scatterplot don"t all line up, but a straight line can summarize the general pattern. The linear model can help us understand how the explanatory (independent) and response (dependent) variables are associated. The regression line is a tool for making predictions about future observations. It is a useful method for summarizing a linear relationship. It is given by an equation for a straight line. y = a + bx where y is the y-variable, x is the x-variable, a is the intercept, and is the slope. To find the regression line we use technology.
