Data Analytics 3

Regression model with two or more variables is:

• Bivariate regression model

• Multiple regression model

• General Least Saquare Model

• no correct answer!!!!

if we have a bivariate equation model, which statistic test should we use?

• t-test

• f-test

• Chi Squared test

• Chow test

Why RRSS is higher than URSS?

• RRSS have restriction than can caused higher residual

• URSS is higher than RRSS, miss :(

• RRSS cause higher degree of freedom

• RRSS can have higher number of parameters

What we can not test using F or t-test?

• b2 *b3 = 2

• b2+b3=1

• b2=0 and b3=0

• all equations can be test using F and t-test miss :)

"searching many series for statistical relationships without theoretical justification"

• Data Mining

• Data Snooping

• Data Cleaning

• Data fitting

Quantile Regression

• Quantile regression estimates the conditional mean of the dependent variable.

• Quantile regression is only useful when the conditional distribution of the dependent variable is symmetric.

• Quantile regression allows for the estimation of the conditional distribution of the dependent variable at various quantiles.

• Quantile regression is equivalent to ordinary least squares regression.

Quantile Regression

• Quantile regression estimates the conditional mean of the dependent variable.

• Quantile regression is only useful when the conditional distribution of the dependent variable is symmetric.

• Quantile regression allows for the estimation of the conditional distribution of the dependent variable at various quantiles.

• Quantile regression is equivalent to ordinary least squares regression.

Quantile Regression

• Quantile regression estimates the conditional mean of the dependent variable.

• Quantile regression is only useful when the conditional distribution of the dependent variable is symmetric.

• Quantile regression allows for the estimation of the conditional distribution of the dependent variable at various quantiles.

• Quantile regression is equivalent to ordinary least squares regression.

Which of the following statements about R² is true?

• R² measures the strength of the linear relationship between the independent and dependent variables

• R² can take values between -1 and 1.

• R² is a measure of the percentage of variation in the dependent variable explained by the independent variables

• R² increases as more variables are added to the regression model