# Inferential statistical testing

- Created by: Thegirlwhoknewtoomuch - Team GR
- Created on: 16-05-14 11:17

First 490 words of the document:

Psychology unit 4 research methods revision

Inferential statistical testing

Used to determine if your results are significant or due to chance. Each test looks

at the sample and the size of the difference between the 2 groups to estimate if

they are different or linked. The accepted level of significance is 5% which means

95% of the time the results are significant and it is possible that the results are

due to chance and not the manipulation of the IV.

Choosing a statistical test

Spearman's rank is used if the study is investigating a correlation. If a

difference was investigated then the level of data (ordinal or nominal).

Chi squared is used if the study is looking for a difference and if the level

of data is nominal (named categories). The score of each category is

described as frequencies.

Mann Whitney U test is used if the study is looking for a difference, if the

level of data used was ordinal and if the type of experimental design used

was independent groups.

Wilcoxon T test is used if the study looks for a difference, if the level of

data is ordinal and if the type of experimental design was repeated

measures.

Spearman's rank: looks at a correlation co-efficient called Rho which is between

+1 and -1. To see if Rho is significant, a significance table is used along with the

number of participants (N) and the type of hypothesis (one or two tailed). To be

significant, Rho needs to be greater than the critical value which means that we

can then reject the null hypothesis and accept the alternate hypothesis and the

significance of the results. The + and symbol in the value of Rho is ignored when

finding if Rho is significant or not (e.g. +0.58 or -0.58).

Chi squared: the calculated value of chi needs to be greater than the critical value

in order to be significant and therefore reject the null hypothesis and accept the

alternate hypothesis. Findings from an investigation involving chi squared are

presented in a contingency table. To calculate the degree of freedom the number

of rows (minus 1) is multiplied by the number of columns (minus 1). This is used to

find the critical value by referring to a critical value table to see if the critical

value is greater than the chi value. If it is then there is a significant difference

between the 2 groups.

Mann Whitney U test: a value for this is calculated. The sample sizes of the 2

groups are needed along with the type of hypothesis to look up the critical value

to see if there is a significant difference. In order to be significant, the value of

U must be lower than the critical value.

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