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Chapter 10 - ECMT1020 Chapter 10 Non-parametric Statistics...

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ECMT1020: Chapter 10 Dr Boris Choy 1 ECMT1020 Chapter 10 Non-parametric Statistics © Dr Boris Choy for ECMT1020
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ECMT1020: Chapter 10 Dr Boris Choy 2 Topics covered 1. Parametric vs Non-parametric statistics 2. Mann-Whitney U test for two independent populations 3. Wilcoxon matched-pairs signed rank test for two dependent populations 4. Kurskal-Wallis test for more than 2 independent populations References Black 17.2, 17.3 & 17.5 Excel file: Chapter 10.xls
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ECMT1020: Chapter 10 Dr Boris Choy 3 Learning Objectives Learning Objectives Learning Objectives Understand the difference between parametric and non-parametric statistics Recognise the advantages and disadvantages of non- parametric statistics Able to perform non-parametric version of hypothesis tests for [1] the means of 2 independent populations [2] the means of 2 dependent populations [3] the means of >2 independent populations
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ECMT1020: Chapter 10 Dr Boris Choy 4 Parametric and Non-parametric Statistics
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ECMT1020: Chapter 10 Dr Boris Choy 5 Hypothesis Testing Hypothesis Testing You must be very familiar with the following hypothesis tests [1] Use the two-sample t -test to test whether the means of two independent normal populations are identical. [2] Use the paired t -test to test whether the means of two dependent normal populations are identical. [3] Use the ANOVA F -test to test whether the means of more than two independent normal populations are identical. Note: These test are valid if the data come from a normal population This is an assumption on the distribution
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ECMT1020: Chapter 10 Dr Boris Choy 6 Parametric and Parametric and Non Non - - parametric Statistics parametric Statistics Parametric statistics are statistical techniques that make assumptions about the population that generates the data. A common assumption is that the data come from a normal population [Of course, other probability distributions can also be assumed.] Parametric statistics use the numerical values of the data
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ECMT1020: Chapter 10 Dr Boris Choy 7 Parametric and Parametric and Non Non - - parametric Statistics parametric Statistics Non-parametric statistics are statistical techniques that impose fewer assumptions about the population that generates the data. Also known as “ Distribution-free statistics ” – make no assumption on the probability distribution. Non-parametric statistics do not use the numerical values of the data. Instead, they use the ranks of the data.
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ECMT1020: Chapter 10 Dr Boris Choy 8 Advantages & Disadvantages of Advantages & Disadvantages of Non Non - - parametric Statistics parametric Statistics Advantages: Some non-parametric statistics can be used to analyse nominal and ordinal data. Non-parametric tests are less complicated computationally than the parametric statistics for small samples .
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