Chapter 14-Part I - Chapter 14 Non-parametric Statistical...

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Chapter 14 : Non-parametric Statistical Inference A whole new world!! This is because non-parametric statistics is a totally new (and different) concept in the domain of statistical inference. Till now, all the statistical procedures that we have used were based on certain assumptions. For example, when we compared two groups or treatments, we assumed that the variable was distributed in the two groups and the sample size was moderately If any of these assumptions failed, we had no other options but to abandon our “statistical quest”. But in reality there may be scenarios where the population response distribution is highly or we just couldn’t gather a large enough sample. Will that mean we cannot do any statistical inference based on that data? Statisticians have long pondered over this problem and in the 1940’s they came up with a new kind of
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statistical procedure which doesn’t depend so much on assumptions (of and ). They named this method “ non- parametric ” or distribution free ”. They are called “distribution free” simply because they donot depend on any particular of the variable. In the earlier methods, if we wanted to compare two groups on a response variable : We selected samples from the two groups. For each of the sample units we measured the response variables. Lastly we compared the of the response variables for the two groups. For non-parametric inference : We will still select independent samples from the two groups. Instead of measuring the response variable for each of the subjects, we will the based on the variable.
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