From Quizes

Question 0

The purpose of defining families of IVs in a model reduction exercise is to:

Answer 0

Let theory play a role in the analysis
Reduces likelihood of a type two error
Maximises chance the theoretically most important predictors will remain in the model
Decrease the number of hypothesis tests conducted

Question 1

Is it possible to obtain an approximate hypothesis test concerning the effect of an IV on a DV from the confidence interval? How?

Answer 1

Yes, if zero doesn’t lie within the 95% ci we will reject the null hypothesis that the population slope is zero.

Question 2

ANOVA - regression suns of squares gives us…

Answer 2

Is the part of the variance that has been accounted by the regression model

Question 3

ANOVA table - std dev given by…

Answer 3

Finding the square root of the mean square error.

Question 4

Assumptions of regression and how we assess them?

Answer 4

1. Independent observations - normally met by design
2. Normal distributions of residuals - via a pp plot - expected (y-axis) vs observed (x-axis), clear snaking around the line?
3. Linear relationship between IV and DV - even # above and below the line? Consistent trend or pattern influencing the data?
4. Constant variance - fanning?

Question 5

How do we get ‘r square’ from sum of squares?

Answer 5

Divide regression SOS into total SOS.

Question 6

Effect of a confounding variable?

Answer 6

The effect of x1 is negated or reduced after controlling for x2

Question 7

Effect of suppression

Answer 7

The effect of x1 is only apparent or is increased after controlling for x2

Question 8

Effect of interaction variable

Answer 8

The effect of x1 is estimated to be larger or smaller depending upon the value of x2

Question 9

Direct & indirect effects of variables?

Answer 9

The effect of x1 acts on Y (at least partially) through x2

Question 10

Collinearity

Answer 10

This occurs when two or more IV’s are so correlated that one can be predicted (almost) exactly from one or more of the others

Question 11

Tolerance and VIF tells us? What values?

Answer 11

Statistical indicator of collinearity. Regresses x1 on all other IV’s and assesses how much of the variance in x1 is not accounted for by the other IV’s. this .1 means there is little to distinguish it from a combination of other IV’s. VIF is inverse of tol.

Question 12

Formula for number of possible pair wise comparisons

Answer 12

(k(k-1))/2 where k is the number of levels

Question 13

In multiple regression, when we control for potentially confounding variables, we…

Answer 13

Estimate the effect of each IV with the other IV(s) held at a non-specified constant

Question 14

In a log regression model, which column gives us the odds ratio

Answer 14

Exp(b)

Question 15

How do we find correlation for the a model looking at the r square stats

Answer 15

Square root the r square stats and it gives you the correlation

Q8 practice exam questions

Question 16

Variance fitted last or unique examined variance is obtained by?

Answer 16

Squaring the part correlation for the corresponding value.

Question 17

If the effect of one IV (e.g. Anger) is suppressed by one or more IVs, we would expect:

Answer 17

The partial regression coefficient for anger to be larger after controlling for the other IV(s)

Question 18

The SD of the residuals on the a model regression can be found from where in the anova table output.

Answer 18

By square rooting the mean square residuals