Before exam

Question 1

Cronbachs alpha output

Answer 1

–Inter-item correlation matrix: Correlation coefficient indicates internal consistency
-Item total statistic table: Corrected item total correlation (remove items below 0.3)
Cronbachs alpha if item deleted: overall alpha if item deleted

Question 2

simple regression output

Answer 2

• model summary: R and R2 (0-1)
• coefficients table: beta values (model parameters)
• ANOVA: model fit (SST3 = SSM1 (variance explained) + SSR2 (error in model))

Question 3

better to use simple regression than mean if

Answer 3

-SSM is greater than SSR (error)

Question 4

Multiple regression output

Answer 4

• Model summary: R= multiple correlation coefficient and R2 = coefficient of multiple determination
• Coefficients table: how much each predictor contributes to an outcome: intercept (b0), b1,b2… (slope)
• ANOVA table: how much the predictors as a set contribute (change in SS = variance explained)

Question 5

Standardised variance

Answer 5

Compare strength and direction across different measures

• predictor on X axis
• Standardized measure of linear relationship
• 1 - +1
• Coefficient of determination (R2) = proportion of variance explained

Question 6

Multiple regression assumptions

Answer 6

• power: large sample
• normal distribution
• durbin Watson
• Multicollinearity
• homoscedacuty
• interval or nominal with two levels
• linear relationship
• must be some variance

Question 7

Stats

Answer 7

Correlation coefficient (R): standardized measure of relationship strength (0-+1)

• Coefficient of determination (R2): proportion of variance explained by model
• Beta coefficient: slope and intercept