Psychology 202 - Test 2 Flashcards Preview

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Flashcards in Psychology 202 - Test 2 Deck (28):
1

hypothesis testing

a statistical method that uses sample data to evaluate a hypothesis about a population

2

hypothesis

the prediction about the relationship between two variables

3

critical value

set cut-off sample score

4

directional hypothesis

make a prediction regarding direction
i.e. increase...or decrease...

5

one-tail test

looking at one tail/extreme of the distribution
- 5% > 1.64
- 1% > 2.33

6

non-directional hypothesis

no prediction regarding direction
- just know there is a change, don't know in/decrease

7

two-tail test

need to look/think about both extremes
- 5% > 1.96
- 1% > 2.57

8

distribution of means

set of sample means from a given population

9

rule #1

the mean of a distribution of means (μm) is the same as the mean of the population of individuals

10

rule #2a

The variance of the distribution of means is the variance of the population of individuals divided by the number of individuals in each sample

11

rule #2b

the standard deviation of the distribution of means is the square root of the variance of the distribution of means

12

rule #3

the shape of the distribution of means is approximately normal if at least one of the conditions is met
- sample size is 30 or more
- the distribution of the population of individual scores is normally distributed

13

Variance & SD formulas for Distribution of Means

variance --> δ²m = δ² / N
SD --> √δ²m = δ² / N or √δ²m

14

z-test

hypothesis testing procedure using the mean of the sample when the population variance is known
- comparing sample mean to distribution of means

15

z-test formula

Z = (M - μm) / δ²

16

statistical significance

the number is so extreme it is unlikely to have gotten it by chance

17

Alpha (α) - Type I Error

- the null is true and the data tells us to reject
i.e. jury finding innocent man guilty

18

Beta (β) - Type II Error

- the null is false and the data tells us to retain it
i.e. jury lets guilty man go free

19

comparing studies

- as long as you have statistical significance, neither score is more than the other

20

practical significance

difference meaningful in real-world context
- one leads to more improvement over other

21

effect sizes

the extent to which population means differ and distributions overlap

22

large effect size

little overlap with vastly different means

23

small effect size

a lot of overlap with different but close means

24

Cohen's D

measure of effect size
- mean and how spread out the distribution is (SD/SE)
- allows us to examine practical significance (how different the groups are) and compare studies

25

effect size cut-offs

small = .2
medium = .5
large = .8

26

statistical power

the probability that a study will yield a statistically significant result if the research hypothesis is really true
- opposite is beta/type II error

27

what affects power

- effect size
- sample size
- significance level (alpha)
- one vs. two tailed tests
- statistical test

28

increase power

- more lenient cut-off (.05 over .01)
- increase sample size
- use one tail
- increase intensity of procedure
- be more precise > less diverse pop., standardized, controlled circumstances/more precise measurement