Statistics

Question 1

sampling bias

Answer 1

when sample isn’t representative of the population

Question 2

3 types of correlational research

Answer 2

1. naturalistic observation
2. survey application
3. documentary research

Question 3

3 categories of descriptive statistics

Answer 3

1. distribution
2. central tendency (mean, median, mode)
3. measures of variability (range, standard deviation, variance)

Question 4

inferential statistics meaning

Answer 4

drawing conclusions about population’s features based on results from test

Question 5

one sample t-test meaning

Answer 5

comparing mean sample of population and small sample taken from population

Question 6

two-sample t-test meaning

Answer 6

comparing mean values of independent sample 1 and independent sample 2

Question 7

paired sample t-test meaning

Answer 7

comparing value of sample 1 at time 1 to value of sample 1 at time 2

Question 8

when do we have strong positive correlation?

Answer 8

When Pearson’s r is bigger than 0.5

Question 9

operational definition meaning

Answer 9

precise description of how variables will be measured

Question 10

true experiment

Answer 10

scientist has complete control over manipulation of IV + random allocation

Question 11

randomised control trial

Answer 11

scientific experiment where similar people allocated to 2 groups to test intervention

Question 12

cross sectional research
benefits
disadvantages

Answer 12

• data collected in one specific point in time to compare subgroups

benefits:
+ compare subgroups

disadvantages:
- no measures over time

Question 13

systematic sampling definition

Answer 13

every nth person gets chosen

Question 14

stratified sample definition

Answer 14

type of random sampling

population divided into groups based on characteristics then randomly selected from those

Question 15

cluster sampling

Answer 15

all population divided into clusters

Question 16

4 non-probability sampling methods

Answer 16

1. non-convenience sampling
2. purposive sampling
3. quota sampling
4. snowball sampling

Question 17

purposive sampling definition

Answer 17

handpicked participants based on their characteristics

Question 18

nominal data definition

Answer 18

data without numerical value

*colours of rainbow
*countries

Question 19

ordinal data definition

Answer 19

categories with specific order that can be ranked

*military ranks
*economy classes

Question 20

continuous variables

Answer 20

numerical that can assume any number

*weight
*temperature

Question 21

interval variables definiition

Answer 21

ordered + quantifiable but with no true zero

• temperature in the sense that 0 celsius isn’t absence of temperature

Question 22

ration intervals

Answer 22

• quantitative but have an actual zero

*height
*income

Question 23

normal distribution characteristics

Answer 23

1. mean = 0
2. SD = 1
3. kurtosis = 3
4. tails touch x axis at infinity (never)

Question 24

one tailed directional hypothesis

Answer 24

predicts direction of effect

reading will equal HIGHER intelligence levels

Question 25

two tailed directional hypothesis

Answer 25

predicts that IV will impact DV but doesn’t say what direction

reading will have direct impact on intelligence levels

Question 26

type 1 error

Answer 26

false positives

• reject null when null is actually true

Question 27

type 2 error

Answer 27

false negative

• accept null hypothesis when alternative actually true

Question 28

2 tests for between groups

Answer 28

• independent samples t-test (parametric)
• mann-whitney U test (non-parametric)

Question 29

parametric meaning

Answer 29

evenly distributed

Question 30

non-parametiric

Answer 30

not evenly distributed

Question 31

2 tests within groups design

Answer 31

1. related samples t-test (parametric)
2. Wilcoxon signed rank test (non-parametric)

Question 32

what does correlation analysis tell us

Answer 32

1. direction
2. strength

Question 33

Pearson’s r

Answer 33

• continuous variables
• perfect correlation at 1 (means data points on straight line)

Question 34

Spearmann rank order correlation (rho)

Answer 34

• ordinal value
  *ranking students’ performance

Question 35

ANOVA

Answer 35

• comparison of more than 2 groups

Question 36

correlation what does it show

Answer 36

• degree of association between 2 variables

Question 37

multiple regression definition

Answer 37

• relationship between multiple IVs on one DV

IV -> predictor variable (continuous or categorical)
DV -> outcome variable (continuous)

Question 38

hypothesis definition

Answer 38

testable prediction of relationship between two or more variables

Question 39

standard deviation

Answer 39

spread of data that shows how scores deviate from the mean

square root of variance

Question 40

variance definition

Answer 40

how scores are distributed around the mean

Question 41

how to reduce type 1 error

Answer 41

• set lower p value

Question 42

to reduce type 2 error

Answer 42

• pick bigger sample size
• increase p-value (increases chance of type 1 error)

Question 43

when to use mann Whitney

Answer 43

for independent samples t-test with non parametric data

Question 44

when to use Wilcoxon

Answer 44

paired samples t-test with non-parametric data

Question 45

does correlation have independent variable?

Answer 45

• NO!

we don’t manipulate any variables just look at the relationship

Question 46

mode what data can it be used for

Answer 46

nominal data

• mode is most common answer