Module 1 + 2

Question 1

analyzing data involves being part (careers)

Answer 1

• good detective
• honest lawyer
• good storyteller

Question 2

what test is used to determine if scores for a sample of ppl are different from a theoretically specified score

Answer 2

single sample t test

Question 3

what test is used to determine if scores for a sample of people are different at two points in time

Answer 3

two sample t test

Question 4

in comparative stats there are _____ or ____ explanations for claims

Answer 4

• systemic, chance
• ex random chance, systemic influence

Question 5

NHST

Answer 5

• Null hypothesis statistical test
• to determine if the observed difference is different than if it were due to chance
• dominate procedure for differentiating chance and systemic influence

Question 6

if you test your hypothesis and determine that chance is ruled out do you ;

a) accept that change is due to systemic reasons only
b) accept that change is due to a combo of chance and systemic reasons

Answer 6

b)

Question 7

ablesons magic criteria

Answer 7

• properties of data, analysis, and presentation that determine strength of research claim
• Magnitude
• articulation
• generality
• interestingness
• credibility

Question 8

random error often evens out in ____ sample sizes

Answer 8

larger

Question 9

the smaller the sample size, the ____ the difference needs to be in order to be significant

Answer 9

larger

Question 10

alpha (0.05 in psyc) can also be referred to as

Answer 10

tolerable difference

Question 11

independent samples t test

Answer 11

• two samples that are independent from one other / drawn from separate populations that are then compared to determine if there is a difference

Question 12

formula for independent samples t test in words

Answer 12

t = sample data - hypothesized population perameter/estimated standard error

Question 13

what do larger t values indicate

Answer 13

• greater likelihood of difference from hypothesized value
• two scored differentiate from one another

Question 14

formula for independent samples t test in symbols

Answer 14

t = (x1-x2)-(μ1-μ2) / SE
or
t= x1-x2/SE

x1/2=means from samples
μ=means from populations

Question 15

in the null hypothesis, μ1-μ2= _____

Answer 15

0, there is no difference between populations

Question 16

standard deviation

Answer 16

• how far your sample is dispersed from the mean
• spread around the average score

Question 17

Standard error formula

Answer 17

Sx= S/√n

Question 18

standard error formula for an independent t test

Answer 18

Sx1-x2=√ (s^2/n1 + s^2/n2)

Question 19

degree of freedom formula

Answer 19

df= (n1-1) + (n2-1)

Question 20

how to use df to calculate a missing number if you have 2/3 numbers and the mean

Answer 20

• there is only one # that can work
• df= unique answer/#
• any property from the sample can be used to determine other value

Question 21

property of sample formula

Answer 21

sample mean (n-1)

Question 22

n

Answer 22

sample size

Question 23

t or f: as df increases, values tend to be spread further from 0

Answer 23

false, they cluster closer to 0 (above 120=df, data is very close)

Question 24

alpha

Answer 24

• probability of messing up that is acceptable
• 5% (0.05)
• 2.5% in each tail of two tail test and 5% in one side in one tailed test

Question 25

because test gives no direction it is called a _______ test, with 2.5% representing the most extreme ____ and ____ values

Answer 25

two tailed, positive and negative

Question 26

type 1 error

Answer 26

- rejecting the null when its true - finding a difference when there is no difference

Question 27

type 2 error

Answer 27

- failing to reject the null hypothesis - finding no difference when there actually is one

Question 28

replication crisis

Answer 28

- ppl doubt psych research because when studies are replicated, different results occur/lower rates occur

Question 29

One tailed tests

Answer 29

- aka directional tests - only considering extreme t values in one direction (ie positive) - rather than 5% in both tails, 5% in one side - more wiggle room - p value is half that of a two tailed test

Question 30

lopsided test

Answer 30

- compromise between one and two tailed tests when researcher has directional prediction - weight the tails of distribution (more liberal for predicted direction and conventional for unexpected direction)

Question 31

what is the widely accepted standard for lopsided tests

Answer 31

- there is none - any as long as you can defend/justify

Question 32

conventional level for type l and type ll errors

Answer 32

- type l: 0.05 - type ll: 0.2

Question 33

power

Answer 33

- 80% is goal/standard - probability that stat test will correctly reject a false null hypothesis - oppositely related to type ll error - power=1-β

Question 34

determinants of power

Answer 34

- alpha level (stricter=lower power, under researcher control) - sample size (larger=bigger power/lower SE, under researcher control) - magnitude of effect/effect size (larger IV effect=bigger power, somewhat under researcher control)

Question 35

how to calculate power of test

Answer 35

- stat tables/programs calculate using: alpha, sample size, and magnitude of effect

Question 36

how can power help with sample size planning

Answer 36

- before a study, can help determine appropriate sample size - specify alpha (0.05) and desired power (0.80), make assumption of magnitude then you can calculate sample size needed to get all the values

Question 37

assumptions about independent samples t tests

Answer 37

- independence of observations - normal distribution for each group - equality of variance in outcome variable across groups

Question 38

repeated measures t test

Answer 38

- testing diff between two means for same sample of ppl - usually longitudinal w/ intervention in between - same outcome under different conditions - aka paired samples t test

Question 39

Sample data difference scores are rep'ed by _____ in equations whereas the mean of different scores is ____

Answer 39

D, D (with line above)

Question 40

formula for repeated measures t test

Answer 40

t= (D_-µD)/S(D_) or t=D_/S(D_) µD=mean of difference scores in population SD_=standard error of sample mean of difference scores

Question 41

in repeated measures t tests, SD_ formula

Answer 41

SD_= S/√n S=standard deviation for difference scores

Question 42

df in a repeated measures t test formula

Answer 42

df= n-1 (because there is only one sample)

Question 43

repeated measures t test assumptions

Answer 43

- each score is independent - difference scores are normally distributed - NOT homogeneity

Question 44

t or f: repeated measures t test are more economical but have a lower power

Answer 44

false, they are more economical and they have higher power

Question 45

pros of repeated measures t tests

Answer 45

- more economical - higher power - no carry over effects - less vulnerable to demand characteristics

Question 46

demand characteristics

Answer 46

- things in experiments that lead participants onto what the researcher is attempting to study - can make good or evil subjects if they determine the hypothesis (both bad in the end)

Question 47

what test is used to compare two means from the same population

Answer 47

paired sample/repeated measures t test

Question 48

scale vs ordnial vs nominal numbers

Answer 48

- scale: theoretically infinite amount of numbers, equal intervals, cont., #s are meaningful - ordinal: categorical, no positions/order, meaningful but not measurable difference (ex always/sometimes/never - nominal: discrete/categorical, not smth you can measure difference of (ex course codes)