Probability distribution and statistics analysis are closely related to each other. For statistics analysis, analysts make predictions based on a certain population, which is mostly under a probability distribution. Therefore, if you find that the data selected for prediction does not follow the exact assumed probability distribution in experiment design, the upcoming results can be refuted. In other words, probability provides the justification for statistics. The following examples will demonstrate how to generate probability distribution in R.

Since most distribution functions originate from the `stats`

package, make sure the library `stats`

are loaded.

Perform the following steps: ...

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