Week 12

Question 1

SE

Answer 1

the SD for the distribution of sample means

For larger samples, the SE gets smaller

Question 2

A-level

Answer 2

Used to define the very unlikely outcomes if the Ho is true
Probability of rejecting the Ho when it is true, or making the wrong decision
AKA level of significance
a=0.05 (5%)

Question 3

critical region

Answer 3

AKA region of rejection
Outcomes that are very unlikely to be obtained if the null hypothesis is true
‘very unlikely’ is determined by ‘a’, and the boundaries are determined by the alpha level
If sample data fall in the critical region, we reject the Ho

Question 4

critical region boundaries

Answer 4

Use a-level and unit normal table and determine the precise z score location of critical region boundaries.
For α = .05, we split 5% into two –>2.5% in each tail. We then calculate z-score corresponding to p = .025 in the tail. Thus,z = ±1.96.

Question 5

one sample t test

Answer 5

One sample t test: population mean known

Question 6

independent t test

Answer 6

compare the means of two independent groups

Question 7

paired t test

Answer 7

compare two means from the same sample

Question 8

effect size

Answer 8

Aim to quantify the magnitude of a relationship or treatment effect

Question 9

cohens d

Answer 9

tells the degree of separation between two distributions; how far apart are the means of two distributions
mean difference/ SD

Question 10

type I error

Answer 10

incorrectly reject the null hypothesis (false positive)

Question 11

Type II error

Answer 11

incorrectly accept the null hypothesis (false negative)

Question 12

statistical power

Answer 12

probability of detecting an effect if there really is one; probability that the hypothesis test will reject the null hypothesis when there actually is a treatment effect

Question 13

ways to increase the power of a study

Answer 13

use a higher a-level 
use a one tailed test 
increase n 
use a within-subjects design 
increase effect size

Question 14

type II error identified by

Answer 14

beta (B)

Question 15

power identified by

Answer 15

1-beta (B)

Question 16

increase power- higher a level

Answer 16

bigger critical region= greater power

BUT increases type I error rate

Question 17

increase power- use one tailed test

Answer 17

with a all in one tail, the critical value is smaller = greater power

Question 18

increase power- increase sample size

Answer 18

more participants=greater power

Question 19

increase power- use a within-subjects design

Answer 19

eliminating individual differences reduces SE

Question 20

increase power- increase the effect size

Answer 20

10 weeks instead of 6 weeks of therapy may result in larger difference

Question 21

parametric statistics

Answer 21

inferential procedures that require certain assumptions about the raw score population represented by the sample; used when we compute the mean

Question 22

non parametric statistics

Answer 22

inferential procedures that do not require stringent assumptions about the raw score population represented by the sample; used with the median and mode