Parametric Tests Of Difference

Question 0

Directional hypothesis are more

Answer 0

Powerful

Question 1

Power refers to

Answer 1

My chances of detecting a sig result

Question 2

Why don’t we use directional hypotheses all the time?

Answer 2

Don’t have enough previous evidence

Question 3

Effect size does not reveal

Answer 3

Significance level. Or size of effect

Question 4

Effect sizes helps you compare data across…

Answer 4

Studies. Ie meta analysis

Question 5

Effect size is the

Answer 5

Magnitude of difference btwn two populations

Question 6

When we get more than two means/groups we use an

Answer 6

ANOVA

Question 7

Z scores are calculated so that you can see

Answer 7

Where a score lies within a sample

Question 8

The smaller the z score then the

Answer 8

More likely that that sample is part of the population

Question 9

If the z score is higher than 1.96 we conclude that the

Answer 9

Sample has not come from the population

Question 10

What is independent design?

Answer 10

Expose diff ppl to diff experimental manipulations

Question 11

What is repeated measures or within-subjects design?

Answer 11

Single group of ppl exposed to different experimental manipulations at different times

Question 12

Dichotomous variables what type of level measurement?

Answer 12

Nominal

Question 13

Dichotomous variables have only ……..types of categories or levels

Answer 13

2 (ie male/female)

Question 14

What is a paired-samples t-test?

Answer 14

Two experimental conditions and the sane participants take part in both conditions

Question 15

If samples come from the same pop then the means will be

Answer 15

Similar

Question 16

If the standard error is small what does that mean the sample means will look like?

Answer 16

Small SE = samples have similar means

Large SE = sample means big diff

Question 17

What does signal to noise ratio mean??

Answer 17

Variance explained by the model / by the variance the model can’t explain OR effect / error

Question 18

What are some of the assumptions we look for in our data before running parametric statistics

Answer 18

Normal distribution
Homogeniety of variance
Level of measurements (interval, ratio)
Outliers

Question 19

T-test is the simplest form of

Answer 19

ANOVA

Question 20

Effect size is looking at the

Answer 20

Relationship btwn the IV & DV.

Question 21

How much variation in our DV can be attributed to our IV…is calculated by the

Answer 21

Effect size

Question 22

Pearsons r is used to calculate the

Answer 22

Effect size

Question 23

When the sample size is less than 30 the shape of the t-distribution is

Answer 23

Flatter than normal distribution. Greater area under tails

Question 24

What is the t-test calculation?

Answer 24

t= observed diff btwn sample means - expected diff btwn pop means divided by est of SE of the diff of the 2 sample means

Question 25

You can look at the upper and lower bounds of the 95% CI to see if your result will be sig. As it will include…….in the range

Answer 25

0

Question 26

Independent test 3 assumptions

Answer 26

Normal distribution
Independence of scores in sample
Homogeneity of variances (levenes must have a non-sig value p=>.05