Why Citing Statistics Matters
In the fields of statistics, psychology, and data science, referencing the source of your data is just as important as citing a quote in an English paper. It allows your readers (and professors) to verify your data, understand the methodology used to collect it, and gives credit to the original researchers or organizations.
1. Citing an Online Statistics Report (APA 7th Edition)
Many undergraduate statistics projects rely on reports from government agencies (like the CDC, WHO, or Census Bureau). The standard format is:
Format: Author/Organization. (Year). Title of report. Publisher (if different from author). URL
Example: Centers for Disease Control and Prevention. (2022). National diabetes statistics report. U.S. Department of Health and Human Services. https://www.cdc.gov/diabetes/data/statistics-report/index.html
2. Citing a Dataset
If you downloaded a raw dataset (e.g., from Kaggle or an academic repository), you should cite it explicitly.
Format: Author/Creator. (Year). Title of dataset (Version number) [Data set]. Publisher/Repository. URL or DOI
Example: Smith, J., & Doe, A. (2023). Global temperature anomalies 1880-2023 (Version 2) [Data set]. Kaggle. https://www.kaggle.com/...
3. Citing Statistical Software (SPSS, R, Python)
When you conduct data analysis for a research paper, you must state which software you used. In APA format, you cite the software itself.
IBM SPSS: IBM Corp. (2021). IBM SPSS Statistics for Windows (Version 28.0) [Computer software]. IBM Corp.
R: R Core Team. (2022). R: A language and environment for statistical computing [Computer software]. R Foundation for Statistical Computing. https://www.R-project.org/
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