T-tests

Question 1

What is beta?

Answer 1

The probability of a type 2 error

Question 2

What happens when you increase alpha?

Answer 2

Beta gets smaller - the chance of a type 2 error gets smaller

Question 3

What is power?

Answer 3

The probability of correctly rejecting a false null hypothesis. 1-β

Question 4

What is a z score?

Answer 4

A score that describes how much an individual deviates from the mean in SD units

Question 5

What is the formula for a z score?

Answer 5

Z=score- mean
SD
Z = x - μ
σ

Question 6

What is the formula for a z test for a sample?

Answer 6

Z = χ - μ

σ/root η

Question 7

What is a z test used for?

Answer 7

It’s the same a z test but for when the population standard deviation is unknown

Question 8

How do you calculate degrees of freedom?

Answer 8

df = N-1

Question 9

What is the formula for a one sample t test?

Answer 9

Τ = χ -μ

s/root n

Question 10

What does the s stand for in the sample t test formula?

Answer 10

S = sample SD

Question 11

What is alpha?

Answer 11

The significance cut off level and the probability of a type 1 error

Question 12

What is the formula for a within subjects t-test?

Answer 12

T = D - O

SD/root n

Question 13

What does the d stand for in the within subjects t test formula?

Answer 13

The difference between the scores

Question 14

What are the assumptions of a between subjects t test?

Answer 14

1. Interval or ratio data
2. Normally distributed
3. Independence of scores
4. Homogeneity of variance

Question 15

What is the homogeneity of variance?

Answer 15

That the 2 groups are equal