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How to understand R language to do normality test analysis, I believe that many inexperienced people are at a loss about this. Therefore, this paper summarizes the causes and solutions of the problem. Through this article, I hope you can solve this problem.

The function commonly used to test normality in R language is shaporo.test (), which is called Shapiro-Wilk (Shapiro-Wilke) normality test.

The corresponding original hypothesis is that the population from sample X has a normal distribution.

Like the code.

> x shapiro.test (x)

Shapiro-Wilk normality test

Data: x

W = 0.99187, p-value = 0.8117

P > 0.05 accept the original hypothesis

Today, a classmate proposed that the output data range of the function shaporo.test () is 3-5000. What should we do if it exceeds 5000? I haven't noticed that the sample size exceeds 5000 before.

The first thing that comes to mind is that among the samples greater than 5000, we can randomly select a sample less than 5000.

Sample code

X

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