Regression Analysis Models for Marketing Decision Making Essay

Regression Analysis Models for Marketing Decision Making - Essay Example Regression analysis is a statistical technique that determines linear relationships between two or more variables. Businesses mainly use regression as a causal inference and for predictions. The major regression models available are linear regression model, non-linear regression model, logistic regression and multinomial logistic regression. Simple regression models use only two variables to achieve a particular statistical result. Multiple linear regression is a regression that applies more than two variables. Logistic regression procedures in quantitative statistics will produce all predictions, residuals and influence statistics. Logistic regression also produces goodness-of-fit tests using sales and marketing data in the case where it has to make predictions for the marketing department. The goodness-of-fit tests are created at the individual case level, and this is regardless of methods of data insertion and whether or not the number of covariate patterns is lesser than the total number of instances in question. On the other hand, multinomial logistic regression procedure aggregates all cases internally to form subpopulations with identical covariate patterns for the predictors, residuals, and goodness-of-tests. Non-linear regression is a quantitative statistical method of finding a nonlinear model of the relationship between the dependent variable and a set of several independent variables. Current non-linear models can be used to estimate models with arbitrary relationships between dependent and independent variables. Iterative estimation is mostly used to achieve non-linear regression. Predicting future marketing trends is business is an essential requirement for the management if they have to beat the competition. This is because a lot of the data is available for use by business nowadays due to advancements in technology like the web that collects a lot of statistical data for analysis. The primary problem facing businesses is identifying the  optimal data analysis model to use in the analysis the quantitative data and getting valid information for predicting the future marketing trends.