# Stats week 1

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• Created by: *rach123
• Created on: 19-01-23 14:13

## Effect size

Size of an effect

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## Sample Size

number of participants

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## Power

probability you will correctly reject the null

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## Statistical power and sample size

A small sample shows only larger effects

A big sample shows smaller effects

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## APA style means and SD

. Report means and SD to 1 decimal place, e.g., 35.1

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## APA test statistics

Report test statistics to 2 decimal places (F, t, R values), e.g., F=3.45

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## APA p values and effect size

Report p-values and effect sizes to 3 decimal places

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## normally distributed

1) Look at histograms

2) look at valued of skewness and kurtosis

3) Look at normality tests

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## skewness and kurtosis

-1.96 <x<1.96 skew or kurtoses

skewness/SE skewness = z skewness

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## normaility

shapiro wilk greater then 0.05

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## Independent t - test

between participant / between subject

- can only be in one group i.e smoker non smoker

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## dependant t test

within participant/ within group

Each participant can be in multiple groups/ conditions

- weight before and after a marathon

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## reporting dependent t-test

There was a significant difference in performance on the math and reading tests, t(76) = 3.75, p < .001, d = .427. By examining the mean scores it can be seen that performance was significantly higher on the reading (19.5 ± 3.5) (mean plus SD) compared to the math (17.9 ± 3.4) test.

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## Reporting Independent t- tests

There was no significant difference in the reading performance of smokers and non-smokers, t(75) = 0.21, p = .831, d = .049.

If Levene’s test is significant, report the results for Welch t test instead (not relevant in this example)

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## Correlations

- assosciation between variables

There is a significant positive correlation between reading test score and house hold income, r(75) = 0.464, p < .001. As household income increases so too does reading test score.

Note DF= N-2

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## reporting one-way ANOVA

• There was no significant effect of transport used and household income, F (2,74) = 3.02, p =.055, np2= .075.

• Note. As the effect is not significant you do not report post-hoc tests

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## non parametric equivalents

P - pearson correlation  NP - Spearman's Correlation

P - Independent T Test   NP- Mann Whitney T-test

P-Dependent T- Test    NP- Wilcoxon Signed- Rank Test

P- One- way ANOVA   NP- Kruskal Wallis Test

P - One-way Repeated Measures ANOVA  NP- Friedman's ANOVA

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