# Inferential statistics

- Created by: Thegirlwhoknewtoomuch - Team GR
- Created on: 20-02-14 13:16

First 471 words of the document:

Inferential statistics

Used to see if your results are significant or if they are due to chance. It looks at

the size of the sample and the size of the difference between the 2 groups to

estimate the likelihood that the 2 groups are really different or linked. Each

statistical test will work out if there is a significant difference. For most

investigations the accepted level of significance is p<0.05 (5%) which means 95%

of the time the results will be significant and there is a 5% chance that the results

were due to chance and not the manipulation of the IV.

Choosing a statistical test

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

difference was investigated then the level of data must be considered

(nominal or ordinal).

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

of data was nominal (named categories) as nominal data is grouped into

categories. The score of each category are described as frequencies.

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

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

independent groups.

Wilcoxon T test is used if the study was looking for a difference, if the

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

repeated measures.

Spearman's rank

Looks at a correlation co-efficient called Rho: this is between +1 and -1. To see if

the Rho is significant a significance table is used long with the number of

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

the Rho needs to be greater than the critical value which means that we can then

reject the null hypothesis and accept the alternative hypothesis and the

significance of the study's results. The critical value is found with the Rho,

number of participants and the type of hypothesis. The + or symbol in the value

of Rho is ignored when finding if the Rho is significant (e.g. +0.58 or -0.58).

Chi squared test

The calculated value of chi needs to be compared to the critical value. If chi is

greater than the critical value then we reject the null hypothesis and there is a

significant difference. Findings from a investigation involving chi squared are

represented 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

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