Linear models and multiple regression

Question 1

residual

Answer 1

variation from regression line (line of best fit), tests underlying assumptions, can be positive/negative, normally distributed/homogenous

Question 2

homogenous residuals

Answer 2

variance around regression line is equal for all predictor variables

Question 3

multiple predictor variables

Answer 3

multiple regression lines, means residuals are closer to the line

Question 4

two way anova

Answer 4

type of multiple regression, both predictors are categorical, calculates residual variance and works r(2)

Question 5

multiple linear regression

Answer 5

can be categorial/continuous, calculates residual variance and r(2)

Question 6

linear models

Answer 6

1 or many predictor variables, response variable always continuous

Question 7

linear regression

Answer 7

1 predictor a continuous variable

Question 8

t test

Answer 8

1 predictor and factor with 2 levels

Question 9

one way anova

Answer 9

1 predictor and a factor with 3 or more levels, compares 3 or more data sets