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Chapter 7 - Analysing the Data Part IV - Analysis of Variance Chapter 1 - Behavioural Science and research Chapter 2 - Research Design Chapter 3 - Collecting the Data Chapter 4 - Analysing the Data Part I - Descriptive Statistics Chapter 5 - Analysing the Data Part II - Inferential Statistics Chapter 6 - Analysing the Data Part III - Common Statistical Tests Probability Sampling distributions Steps in hypothesis testing Type I and Type II decision errors Power Bonferroni Confidence Intervals Readings and links

 

Chapter 5: Analysing the Data
Part II : Inferential Statistics

 

Null and alternative hypotheses

The logic of traditional hypothesis testing requires that we set up two competing statements or hypotheses referred to as the null hypothesis and the alternative hypothesis. These hypotheses are mutually exclusive and exhaustive.

Ho: The finding occurred by chance

H1: The finding did not occur by chance

The null hypothesis is then assumed to be true unless we find evidence to the contrary. If we find that the evidence is just too unlikely given the null hypothesis, we assume the alternative hypothesis is more likely to be correct. In "traditional statistics" a probability of something occurring of less than .05 (= 5% = 1 chance in 20) is conventionally considered "unlikely".

 

 

 

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