R language detection data normal distribution _r language

Input

Comments

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NX <-C (Rnorm (10))

Randomly generates 10 normal distributions of data

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Nx

View NX

[1] -0.83241783-0.29609562-0.06736888-0.02366562 0.23652392 0.97570959

[7]-0.85301145 1.51769488-0.84866517 0.20691119

View the results

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Shapiro.test (NX)

Shapiro-wilk method for normal state test

Shapiro-wilk normality Test

Data:nx

W = 0.9084, P-value = 0.2699

Test results because W is close to 1

The P value is greater than 0.05, so the data is a normal distribution and the results of the origin statistic are the same (below)

The normal detection of the Case II-R language Band (Kolmogorov-smirnov method)

Input

Comments

>

NX <-C (Rnorm (10))

Randomly generates 10 normal distributions of data

>

Nx

View NX

[1] -0.83241783-0.29609562-0.06736888-0.02366562 0.23652392 0.97570959

[7]-0.85301145 1.51769488-0.84866517 0.20691119

View the results

>

Ks.test (NX, "pnorm", mean = Mean (NX), SD = sqrt (var (nx))

Shapiro-wilk method for normal state test

Kolmogorov-smirnov test requires three input variables, and the data itself, mean and standard deviation

One-sample Kolmogorov-smirnov Test

Data:nx

D = 0.1828, P-value = 0.8344

Alternative hypothesis:two-sided

Test results, because

P value is greater than 0.05, so the data is normal distribution, and the results of origin statistics are the same