Stats tests but better explained

Question 1

stats tests

(test for differences)

Nominal data for a repeated measures study:

Answer 1

Chi square

(non-parametric)

Question 2

Stats tests
Test of Correlation

Nominal Data

Answer 2

No

Question 3

Stats tests
Test of Differences

Ordinal data for a Independent measures design:

Answer 3

Mann Whitney U

(Non-parametric)

Question 4

Stats tests
Test for Differences

Ordinal data for Repeated measures design:

Answer 4

Wilcoxon T

(Non-parametric)

Question 5

Stats tests
Test of Correlation

Ordinal data

Answer 5

Spearman’s Rho

(Non-parametric)

Question 6

Stats test
Test of Correlation

Interval/ Ratio data:

Answer 6

Pearson’s R

(Parametric)

Question 7

Stats test
Level of Significance + how to read Critical Value table

Answer 7

in psych

ALWAYS to p<0.05

as this means its 95% likley its significant

and 5% chance the result was due to chance

the location of p<0.05 will be different depending on whether the study has a one or two tailed hypothesis
so always check this

once the correct p<0.05 collum has been identified

the row can be located by counting from the top downwards
the number of participents in the study
once the row has been located
cross between the identifed row and collum to obtain the Critical Value

now you have the observed value from the stats test and the critical value from the table

you can identify whether the test was significant
if the Observed Value is Higher/lower (depending on the test) than the Critical Value

figuring out whether it should be higher or lower can be seen be locating p<0.01 which will be either higher or lower than p<0.05
if it is higher then higher is significant and vice versa

Question 8

Stats Test
Practical + stat test for each topic

Answer 8

Cog
Lab study to test effects of location on recall

Quant
Man Whitney U Wilcoxon T

Learning

Observation of prosocial behaviour gender diff

Quant + Qual
Chi square Thematic Analysis

Bio
Correlation of sleep and aggression

Quant
Spearman’s Rho

Social
Questionaire, Gender diff in Attitudes of Obedience and Authority figs

Quant + Qual

Measures of Central tendency, Dispersion
Standard deviation

Question 9

Stats test
Levels of Measurment

Nominal data

Answer 9

Nominal data is categorised data

which is mutually exclusive
As the data can’t be in both frequency talies in those categories

e.g. Students who go to King eds or Dudley

Freq cant be in both categorys
so mutualy exclusive

but also still categorys and freq

Question 10

Stats test
Levels of Measurment

Ordinal data

Answer 10

Ordinal data is when data is ranked to make it ordinal

e g best to worst

but you don’t know anything about the intervals between these rankings

it doesn’t say how close the ranks are

for example

ranking your knowledge of language level

all you know is that Advanced > intermediate

but have no scale to how much it is more so
dont know how close the ranks are

Question 11

Stats test
Levels of Measurment

Interval data

Answer 11

Interval data

is data ranked in equal intervals

E.G.
temperature in Celsius

there is no true zero in this type of data
meaning therefore there can be - values

e.g. -5°C

but unlike ordinal data
we know what the intervals between the ranks are

e.g we know 5°C is higher than 1°C
and we know that it is higher by 4°C

the intervals between ranks are always equal

1C 2C 3C

not 1C 2C 2.5C 3C

Question 12

Stats test
Levels of Measurment

Ratio data

Answer 12

Ratio data

is data that is ranked in equal intervals

similar to interval data

however is a true zero in this version for example

age
height
weight
or temperature in kelvins

as cannot be - values in these

we know intervals between ranks

+ intervals are the same length