Multiple regression is a statistical way to try to control for this; it can answer questions like, "If sand particle size (and every other measured variable) were the same, would the regression of beetle density on wave exposure be significant? "
-BIVARIATE REGRESSION ANALYSIS is a type of regression in which only two variables are used in the regression, predictive model. -ONE VARIABLE is termed the DEPENDENT VARIABLE (Y), the other is termed the INDEPENDENT VARIABLE (X)
-The regression model, intercept (a), and slope (b) must always BE TESTED FOR STATISTICAL SIGNIFICANCE, since we are estimating them with a sample. We are interested in the values of B and A in the population
YOU CAN STOP HERE. -It is a measure of the STRENGTH OF THE LINEAR RELATIONSHIP between the independent and dependent variable. It is an indication of how well the independent variables can predict the dependent variable in multiple regression Note: Y must be a METRIC VARIABLE.