The statement "Regression of x on y is 4x-3y=8" means that there is a relationship between the variables x and y, and the equation 4x-3y=8 is used to model this relationship. This equation is known as the regression line, which can be used to predict the value of y for a given value of x.
Regression analysis is a statistical method used to examine the relationship between a dependent variable (usually denoted as y) and one or more independent variables (usually denoted as x). It is used to understand how the value of the dependent variable changes when the independent variables are varied.
The regression line is calculated using a method called least squares regression. This involves finding the line that minimizes the sum of squared distances between each data point and the line. This line is also known as the line of best fit.
The slope in regression analysis represents the change in the dependent variable (y) for every unit increase in the independent variable (x). In other words, it shows the rate of change of the dependent variable with respect to the independent variable.
The intercept in regression analysis represents the value of the dependent variable (y) when the independent variable (x) is equal to 0. It is the point where the regression line crosses the y-axis. It can also be interpreted as the baseline value of the dependent variable before any changes in the independent variable occur.