Simple Linear Regression Lecture 8 Like correlation, there are two major Simple Linear assumptions Regression The relationship should be linear, and The level of data must be continuou Simple Linear Regression The regression equation (Bivariate Regression) The purpose of simple linear looked at measuring relationships to fit a line to the two variables this line is between two interval variables using correlation called the line of best fit, or the Now we continue to look at the bivariate analysis of the two variables using regression analysis regression line. When we do a scatterplot However, the purpose of doing regression rather of two variables, it is possible to fit a line than correlation is that we can predict results in which best represents the data one variable based on another variable. so rather than simply see if the variables are related, we can interpret their effect1 1 Lecture 8 Simple Linear Regression 2 Simple Linear Regression (Bivariate Regression) We already looked at measuring relationships between two interval variables using correlation. Now we continue to look at the bivariate analysis of the two variables using regression analysis. However, the purpose of doing regression rather than correlation is that we can predict results in one variable, based on another variable. So, rather than simply see if the variables are related, we can interpret their effect. 2 3 Simple Linear Regression Like correlation, there are two major assumptions: • The relationship should be linear; and • The level of data must be continuous 4 The regression equation The purpose of simple linear regression is to fit a line to the two variables. This line is called the line of best fit, or the regression line. When we do a scatterplot of two variables, it is possible to fit a line which best represents the data