## Abstract

This chapter is designed as an introductory tutorial of common statistical analysis for air pollution data using R, a popular statistical software. This chapter is useful for readers who have minimal knowledge of statistical programming in R as programming codes are provided. This chapter also explains the general concepts of popular statistical analysis methods specifically for air pollution data, which can be useful for readers of nonstatistical backgrounds. The chapter is organized as follows: first, we introduce the characteristics of air pollution data and challenges of statistical analysis for such data. Then we present descriptive analysis and graphical presentation of air pollution data. Finally, we present general concepts and analysis of time series data. In summary, the chapter introduces general statistical concepts and methods, and gives hands-on data analysis illustrations and demonstrations with programming codes, results, and interpretations.

Original language | American English |
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Journal | Spatiotemporal Analysis of Air Pollution and Its Application in Public Health |

DOIs | |

State | Published - Nov 22 2019 |

## Keywords

- Air pollution
- Biostatistics
- Descriptive analysis
- Time series analysis

## DC Disciplines

- Biostatistics
- Environmental Public Health
- Epidemiology
- Public Health