Hypothesis testing

Question 1

Inferential statistics

Answer 1

Used to decide about the population, based on observations of the sample

Question 2

Characteristics of the population

Answer 2

paramaters

Question 3

Characteristics of the sample

Answer 3

statistics

Question 4

mean and sd of the population

Answer 4

μ and σ

Question 5

mean and sd of the sample

Answer 5

x(bar) and s

Question 6

Standard error of the mean

Answer 6

the degree to which means differ from one sample to another

Question 7

If σ is large…

Answer 7

there is a lot of variability between sample means

Question 8

Null hypothesis

Answer 8

the treatment has no effects and the observed mean is drawn from the original population

Question 9

the alternative hypothesis

Answer 9

the treatment has an effect and the observed mean is drawn from a different population

Question 10

Significance level

Answer 10

is also known as the alpha level.

it is the probability value that defines the boundary between rejecting and retaining the null hypothesis

Question 11

if p < alpha….

Answer 11

we reject the null hypothesis

Question 12

Region of rejection

Answer 12

the proportion of area in a sampling distribution that represents the sample means that are improbable if the null hypothesis is true

Question 13

what our critical value for the region of rejection if p=0.05?

Answer 13

z=1.64

Question 14

When is a one-tailed test used?

Answer 14

When there is evidence to suggest that the treatment will an effect in a particular direction
- must be decided before the experiment!

Question 15

when is a two-tailed test used?

Answer 15

when there is no reason to predict the direction of the effect

Question 16

Type I error

Answer 16

rejecting the null hypothesis when is it true

Question 17

what is the probability of making a type I error?

Answer 17

alpha = region of rejection

Question 18

Type II error

Answer 18

retaining the null hypothesis when it is false

Question 19

what is the probability of making a type II error?

Answer 19

beta

Question 20

true or false - you can both type II and type I errors?

Answer 20

FALSE - they are mutually exclusive

Question 21

What does minimising type II errors mean?

Answer 21

reducing beta and increasing power (1- beta)

Question 22

How can we increase power? (four ways)

Answer 22

1. increase alpha
2. increase n (sample size)
3. use powerful statistical tests
4. have a good experimental design

Question 23

How can we get the standard error of the mean when we don’t know the population parameters?

Answer 23

by using an estimate based on the sample

Question 24

Simple sample t-test

Answer 24

a parametric procedure used to test the null hypothesis for a single-sample experiment when the sd of the population must be estimated

Question 25

Student’s t-test

Answer 25

a parametric procedure for small samples

Question 26

Degrees of freedom

Answer 26

n-1

how many scores in the sample are free to vary (all the scores except the last one)

Question 27

Three assumptions we make when using a single-sample t-test

Answer 27

1. the random sample comprises interval or ratio scores
2. the distribution of individual scores is normal
3. the sd of the mean is estimated using the sample

Question 28

two-sample t-test

Answer 28

a parametric procedure in which we compare the difference between two sample means