Users' questions

What is the general equation for a multiple regression with two predictors?

What is the general equation for a multiple regression with two predictors?

analysis using X1 and X2 as predictors of Y provides additional information about three- variable research situations. In Chapter 9, a two-dimensional graph was used to diagram the scatter plot of Y values for each value of X. The regression prediction equation Y′ = b0 + bX corresponded to a line on this graph.

Can you have two predictor variables?

Many outcomes are possible when two variables are used as predictors in a multiple regression. The overall regression analysis can either be significant or not significant, and each predictor variable may or may not make a statistically significant unique contribu- tion.

Can you have 2 dependent variables in multiple regression?

Yes, this is possible and I have heard it termed as joint regression or multivariate regression. In essence you would have 2 (or more) dependent variables, and examine the relationships between independent variables and the dependent variables, plus the relationship between the 2 dependent variables.

How many predictors can you have in a multiple regression?

In statistics, the one in ten rule is a rule of thumb for how many predictor parameters can be estimated from data when doing regression analysis (in particular proportional hazards models in survival analysis and logistic regression) while keeping the risk of overfitting low.

Can you have more than one predictor in multiple regression?

However, in multiple regression, we are interested in examining more than one predictor of our criterion variable. Often this is done to determine whether the inclusion of additional predictor variables leads to increased prediction of the outcome variable.

When do you use a multiple regression formula?

In order to predict the dependent variable, multiple independent variables are chosen, which can help in predicting the dependent variable. It is used when linear regression is not able to do serve the purpose.

How is multiple regression used to predict yield?

As the value of the dependent variable is correlated to the independent variables, multiple regression is used to predict the expected yield of a crop at certain rainfall, temperature, and fertilizer level.

Which is an example of a multiple linear regression?

The multiple linear regression enables analysts to determine the variation of the model and each independent variable’s relative contribution. Multiple regression is of two types, linear and non-linear regression. The multiple regression with three predictor variables (x) predicting variable y is expressed as the following equation: