Irfan Ahmed, PhD

Sometimes you may want to explain variability in a continuous DV using several different continuous IVs. Multiple regression allows us to build an equation predicting the value of the DV from the values of two or more IVs. The parameters of this equation can be used to relate the variability in our DV to the variability in specific IVs. Sometimes people use the term multivariate regression to refer to multiple regression, but most statisticians do not use .multiple" and .multivariate" as synonyms. Instead, they use the term .multiple" to describe analyses that examine the effect of two or more IVs on a single DV, while they reserve the term .multivariate" to describe analyses that examine the effect of any number of IVs on two or more DVs. The general form of the multiple regression model is Y i = β 0 + β 1 X i1 + β 2 X i2 + . + β k X ik + å i,. The elements in this equation are the same as those found in simple linear regression, except that we now have k differe