The R language, as the descendant of the statistics language, S, has become the preferred computing language in the field of statistics. Moreover, due to its status as an active contributor in the field, if a new statistical method is discovered, it is very likely that this method will first be implemented in the R language. As such, a large quantity of statistical methods can be fulfilled by applying the R language.
To apply statistical methods in R, the user can categorize the method of implementation into descriptive statistics and inferential statistics:
- Descriptive statistics: These are used to summarize the characteristics of the data. The user can use mean and standard deviation to describe numerical data, and use frequency and percentages to describe categorical data.
- Inferential statistics: Based on the pattern within sample data, the user can infer the characteristics of the population. The methods related to inferential statistics are for hypothesis testing, data estimation, data correlation, and relationship modeling. Inference can be further extended to forecasting, prediction, and estimation of unobserved values either in or associated with the population being studied.
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