LINEAR REGRESSION JAMOVI

Question 1

0 value indicates the expected and actual
values match precisely

Answer 1

Root Mean Square Error (RMSE)

Question 2

more accurate predictions and fit data well

Answer 2

low RMSE values

Question 3

less accurate predictions, more significant mistakes, fewer accurate forecasts

Answer 3

high RMSE values

Question 4

Durbin-Watson Test
Variance Inflation Factor (VIF)

Answer 4

Jamovi Output: Assumption Checks

Question 5

a test for autocorrelation in a regression
model’s output

Answer 5

Durbin-Watson Test

Question 6

ranges from zero to four

Answer 6

Durbin-Watson Test

Question 7

zero autocorrelation

Answer 7

2.0

Durbin-Watson Test

Question 8

positive autocorrelation

Answer 8

below 2.0

Durbin-Watson Test

Question 9

negative autocorrelation

Answer 9

above 2.0

Durbin-Watson Test

Question 10

correlating a variable by itself

Answer 10

autocorrelation

Question 11

measure of collinearity in the variables

Answer 11

Variance Inflation Factor (VIF)

Question 12

not correlated

Answer 12

equal to 1

Variance Inflation Factor (VIF)

Question 13

moderately correlated

Answer 13

between 1 and 5

Variance Inflation Factor (VIF)

Question 14

highly correlated

Answer 14

greater than 5

Variance Inflation Factor (VIF)