What is Data Mining? Justify the use of data mining to support the use of multiple regression.

An assumption of regression analysis is homoscedasticity, which states that the      residuals exhibit no patterns across values for the dependent variable.     relationship between the independent and dependent variables is linear.     residuals exhibit no patterns across values for the independent variable.     variation of the dependent variable is the same across all values for the independent variable.

Explain what are the least-squares line and Regression?

what does regression analysis mean?  What can you tell from it?

In multiple regression analysis, explain why the typical hypothesis that analysts want to test is whether a particular regression coefficient (B) is equal to zero (H0: B = 0) versus whether that coefficient is not equal to zero

Give an example of how a nonrepresentative sample can severely affect a regression analysis.

Ordinal data cannot be analyzed using regression analysis.  True  False

How is multiple linear regression different from simple linear regression?     Multiple regression involves 2 or more dependent variables.     Multiple regression involves 2 or more independent variables.     Multiple linear regression involves a numeric independent variable and a categorical DV.     Multiple linear regression has more levels.

Describe the correlation coefficient and explain how it is used in regression analysis?

In multiple regression, you can have nominal and continuous predictors true or false