Regression is the study of relationships among variables, a principal purpose of which is to predict, or estimate the value of one variable fromknown or assumed values of other variables related to it.
Variable of inerest: to make predictions or estimates we must idendify the effective predictors of the variable of interest: which variables are important indicators and can be measured at the least cost, which carry only a little informaiton, and which are redundant. Predicting the future: predicting a change over time or extrapolating from present conditons to furture conditions is not the function of regression analysis. To make estimate of the future, use time series analysis.
Linear regression models are used in a variety of business situations to determine relationships between variables that analysts believe intuitively to be related. Regresson analysis involves gathering sufficient data to dtermine the relationship between the variables.
Multiple regression: where there are two or more predictors, multiple regression analysis is employed.
Subscribe to:
Post Comments (Atom)
I think the most difficult part is what should be included in regression analysis. When most of time we tend to use "daily common sense" to do analysis. The result could be either totally wrong or misleading.
ReplyDelete