Make up a multiple regression problem using at least 3 independent variables.Indicate the expected sign (negative or positive) for all slopes and the reasoning behind your hypothesis.For instance if I was going to predict the selling price of a home I might believe the age of the home in years might be a good predictor of the selling price.I could hypothesis that as age increases, selling price would decrease or increase.Whatever I decided, I would explain why I believe the slope would be positive or negative.You do not need to make up data or solve the regression just identify the response variable and all variables considered to help predict this variable even if not used in the final model. STEPS IN MULTIPLE REGRESSION

The steps in multiple regression are basically the same as in simple regression.

1. State the research hypothesis.

2. State the null hypothesis

3. Gather the data

4. Assess each variable separately first (obtain measures of central tendency and dispersion; frequency distributions; graphs); is the variable normally distributed?

5. Assess the relationship of each independent variable, one at a time, with the dependent variable (calculate the correlation coefficient; obtain a scatter plot); are the two variables linearly related?

6. Assess the relationships between all of the independent variables with each other (obtain a correlation coefficient matrix for all the independent variables); are the independent variables too highly correlated with one another?

7. Calculate the regression equation from the data

8. Calculate and examine appropriate measures of association and tests of statistical significance for each coefficient and for the equation as a whole

9. Accept or reject the null hypothesis

10. Reject or accept the research hypothesis

11. Explain the practical implications of the findings