次級資料分析（Secondary data analysis）是使用既有的統計資料來對研究主題進行實證分析的社會研究方法，而既有的統計資料包含人口普查及各種大型學術資料庫，例如台灣社會變遷基本調查計畫。相對於蒐集初級資料（Primary data）而進行的研究，使用次級資料的優勢為：(1) 研究者為取得大型樣本的資料所需花費的時間及金錢成本較低；(2) 資料庫的蒐集通常已採用隨機抽樣原則，分析該類資料的研究成果將能推論至整體社會；(3) 資料庫的蒐集通常為跨時間及跨區域，可用來檢驗跨時變化或跨域比較的研究主題。隨著網路介面的發達及電腦運算速度的提升，對於可公開下載的次級資料庫的運用更是日益方便，次級資料分析便成為當前常見的社會學研究方法之一。

目前社會科學常使用的統計軟體相當多元，但通常以使用者付費的為主。R 是一個程式語言且為少數免付費、開放原始碼（open-source）及跨平台的統計運算及繪圖軟體，它可在 Microsoft Windows、Mac OS 及多數 UNIX 平台上運作。它的操作介面雖然完全以程式語言控制，但學習門檻低，可以作為學習程式語言邏輯的入門，且其繪製的圖表常能見於學術期刊上。R 的擴充性強，有各種套件（packages）及說明檔案可供下載使用來進行統計分析；資料讀取也與其他統計軟體的格式相容，可讀取的格式包括純文字檔、Microsoft Excel、SAS、SPSS、Stata 等。

Secondary data analysis is a social research method that uses existing statistical data to conduct empirical analysis of research topics. Existing statistical data include the census and various large academic databases, such as the Taiwan Basic Survey Project on Social Change. Compared with research conducted by collecting primary data, the advantages of using secondary data are: (1) Researchers spend less time and money to obtain data on large samples; (2) The collection of databases usually adopts the random sampling principle, and the research results of analyzing such data can be extrapolated to the entire society; (3) The collection of databases is usually across time and across regions, and can be used to examine research topics that change across time or compare across domains. With the development of network interfaces and the improvement of computer computing speed, the use of publicly downloadable secondary databases has become increasingly convenient, and secondary data analysis has become one of the common sociological research methods currently.

Currently, the statistical software commonly used in social sciences is quite diverse, but most of them are user-pay software. R is a programming language and one of the few free, open-source, and cross-platform statistical computing and graphics software that can run on Microsoft Windows, Mac OS, and most UNIX platforms. Although its operation interface is completely controlled by programming language, the learning threshold is low and can be used as an introduction to learning programming language logic, and the charts it draws can often be seen in academic journals. R is highly scalable, with various packages and documentation files available for download and use for statistical analysis. Data reading is also compatible with the formats of other statistical software. The formats that can be read include plain text files, Microsoft Excel, SAS, SPSS, Stata, etc.

(1) Liahna E. Gordon, 2016, "Real research; research methods sociology students can use". Thousand Oaks: Sage.

(2) Li, Quan, 2019, "Using R For Data Analysis In Social Sciences: A Research Project-oriented Approach", Oxford University Press.

(3) Verzani, John, 2014, "Using R for Introductory Statistics", CRC Press.

(4) 蔡佳泓，2015，《基礎統計分析：R 程式在社會科學之應用》。臺北：雙葉。

(5) 吳明隆，2015，《R統計軟體應用分析實務》。台北：五南。

(6) Jared P. Lander, 2017, "R for everyone: Advanced Analytics and Graphics". Addison-Wesley.

(1) Liahna E. Gordon, 2016, "Real research; research methods sociology students can use". Thousand Oaks: Sage.

(2) Li, Quan, 2019, "Using R For Data Analysis In Social Sciences: A Research Project-oriented Approach", Oxford University Press.

(3) Verzani, John, 2014, "Using R for Introductory Statistics", CRC Press.

(4) Cai Jiahong, 2015, "Basic Statistical Analysis: Application of R Program in Social Sciences". Taipei: Futaba.

(5) Wu Minglong, 2015, "R Statistical Software Application Analysis Practice". Taipei: Wunan.

(6) Jared P. Lander, 2017, "R for everyone: Advanced Analytics and Graphics". Addison-Wesley.