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ANA600 v1

Module 3 Required Resources

Textbook

R for Data Science
Wickham, H., Çetinkaya-Rundel, M., and Grolemund, G. (n.d.). R for Data Science (2e digital ed.).

9. Layers – R for Data Science (2e) This section will delve deeper into creation of data visualizations in R.
11. Communication – R for Data Science (2e) Sections 11. 1 and 11.2 (only) will detail how to add labels to R visualizations.
10. Exploratory Data Analysis – R for Data Science (2e) This section will review Exploratory Data Analysis, including evaluation of variation and covariation in data.

Learning Statistics with R
Navarro, D. (n.d.). Learning Statistics with R.

Sections 15.1 and 15.2 (only) will discuss linear regression and the lm() function used to perform it in R.

Module 3 Optional Resources

Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python
Bruce, P., Bruce, A., Gedeck, P. (2020). Practical Statistics for Data Scientists: 50+ Essential Concepts Using R and Python(2nd ed.). O'Reilly Media.

Read Chapter 4, Pages 141-150. These pages will provide an additional overview of linear regression and evaluation of error.

Last Updated: Feb 13, 2025 8:16 AM
URL: https://resources.nu.edu/ANA600
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Subjects: Statistics & Data

Tags: data analytics, programming