psyc 60 steiner quiz 3

studied byStudied by 185 people
5.0(4)
Get a hint
Hint

central limit theorem

1 / 44

flashcard set

Earn XP

Description and Tags

chps 12 13 14

45 Terms

1

central limit theorem

the theorem that specifies the nature of the sampling distribution of the mean

New cards
2

central limit theorem definition

given a population with a mean μ and a variance σ², the sampling distribution of the mean will have a mean equal to μ and a variance equal to σ²/N.

  • The distribution will approach the normal distribution as N, the sample size, increases (this sentence is true regardless of the shape of the population distribution)

New cards
3

if you increase the sampling size,

the distribution becomes more normal (bell-shaped)

New cards
4

5 factors that affect whether the t-value will be statistically significant

  1. the difference between X̄ and μ

  2. N (sample size)

  3. S (standard deviation)

  4. α

  5. one-tailed vs two-tailed tests

New cards
5

the difference between X̄ and μ

the greater the difference, the more likely you'll have statistical significance

New cards
6

N

the greater the sample size, the more likely you'll have statistical significance

  • critical value becomes smaller

New cards
7

S

the greater the standard deviation, the less likely you'll have statistical significance

New cards
8

α

the greater the alpha (the larger the rejection region), the more likely you'll have statistical significance

New cards
9

one-tailed vs two tailed tests

  • if you're using a one-tailed test and you're right about the direction, you're more likely to have statistical significance because you've doubled the area of the rejection region

  • if you're using a one-tailed test and you're wrong about the direction, you'll never have statistical significance because the area of the rejection region is 0

New cards
10

effect size

the difference between 2 populations divided by the standard deviation of either population

  • it is sometimes presented in raw score units (and sometimes in standard deviations)

New cards
11

effect size in terms of standard deviations

d^= X̄ - μ / S

New cards
12

guidelines for interpreting d^

trivial, small, medium, large effect size

New cards
13

< 0.2

trivial effect size

New cards
14

≥ 0.2 & < 0.5

small effect size

New cards
15

≥ 0.5 & < 0.8

medium effect size

New cards
16

≥ 0.8

large effect size

New cards
17

confidence interval

an interval, with limits at either end, having specified probability of including the parameter being estimated

New cards
18

Confidence Interval

X̄± t_df * S/√N

New cards
19

what makes a confidence interval wider?

  • smaller α (0.05 to 0.01)

  • larger s

  • smaller N

New cards
20

what makes a confidence interval narrower?

  • bigger α

  • smaller s

  • bigger N

New cards
21

related samples

an experimental design in which the same subject is observed under more than one treatment

ex: comparing students' two sets of quiz scores (DV) after they used two different studying strategies

New cards
22

repeated measures

data in a study in which you have multiple measurements for the same participants

ex: measuring a person's cortisol level before and after a competition

New cards
23

matched samples

an experimental design in which the same subject is observed under more than one treatment

ex: asking a husband and wife to each provide a score on marital satisfaction

New cards
24

d‾

the difference of the means

New cards
25

S_D

the standard deviation of the difference scores

New cards
26

difference scores (gain scores)

the set of scores representing the difference between the subjects' performance on two occasions

New cards
27

advantages of related samples

  1. it avoids the problem of person-to-person variability

  2. it controls for extraneous variables

  3. it requires fewer participants than independent samples designs to have the same amount of power

New cards
28

disadvantages of related samples

  1. order effect

  2. carry-over effect

New cards
29

order effect

the effect on performance attributable to the order in which treatments were administered

ex: you want to know if stimulant A or B improves reaction time more

New cards
30

carry-over effect

the effect of previous trials (conditions) on a subject's performance on subsequent trials

ex: you want to know if Drug A or B improves depression more

New cards
31

independent-sample t tests

are used to compare two samples whose scores are not related to each other, in contrast to related-samples t tests

ex: comparing male and female grades on a language verbal test

New cards
32

two assumptions for an independent-samples t test

  1. homogeneity of variance

  2. the samples come from populations with normal distributions

New cards
33

homogeneity of variance

the situation in which two or more populations have equal variances

  • the variance of a sample is similar to another

New cards
34

heterogeneity of variance

a situation in which samples are drawn from populations having different variances

New cards
35

homogeneity assumption is for

population variances, not sample variances

New cards
36

the samples come from populations with normal distributions

however, independent-samples t tests are robust to a violation of this assumption, especially with sample sizes less than 30

New cards
37

pooled variance

a weighted average of separate sample variances

New cards
38

standard error of difference between means

the standard deviation of the sampling distribution of differences between means

New cards
39

sampling distribution of differences between means

the distribution of the differences between means over repeated sampling from the same populations

New cards
40

degrees of freedom for one-sample t test

N-1

New cards
41

degrees of freedom for related-samples t test

N-1

New cards
42

degrees of freedom for independent-samples t test

n1+n2-2 or N-1

New cards
43

formula for pooled variance

^

<p>^</p>
New cards
44

formula for independent-samples t test

^

<p>^</p>
New cards
45

counterbalancing

how to solve the problems of order and carry-over effect (disadvantages)

New cards

Explore top notes

note Note
studied byStudied by 70 people
Updated ... ago
4.0 Stars(1)
note Note
studied byStudied by 54 people
Updated ... ago
5.0 Stars(1)
note Note
studied byStudied by 361 people
Updated ... ago
4.7 Stars(3)
note Note
studied byStudied by 13 people
Updated ... ago
5.0 Stars(1)
note Note
studied byStudied by 110 people
Updated ... ago
5.0 Stars(2)
note Note
studied byStudied by 19 people
Updated ... ago
5.0 Stars(1)
note Note
studied byStudied by 3 people
Updated ... ago
5.0 Stars(1)
note Note
studied byStudied by 10647 people
Updated ... ago
4.7 Stars(34)

Explore top flashcards

flashcards Flashcard29 terms
studied byStudied by 3 people
Updated ... ago
5.0 Stars(1)
flashcards Flashcard47 terms
studied byStudied by 3 people
Updated ... ago
5.0 Stars(1)
flashcards Flashcard78 terms
studied byStudied by 14 people
Updated ... ago
5.0 Stars(1)
flashcards Flashcard85 terms
studied byStudied by 16 people
Updated ... ago
5.0 Stars(2)
flashcards Flashcard78 terms
studied byStudied by 5 people
Updated ... ago
5.0 Stars(1)
flashcards Flashcard46 terms
studied byStudied by 93 people
Updated ... ago
5.0 Stars(2)
flashcards Flashcard227 terms
studied byStudied by 8 people
Updated ... ago
5.0 Stars(1)
flashcards Flashcard34 terms
studied byStudied by 9 people
Updated ... ago
5.0 Stars(3)