TIM-6130: Data Mining

Ding, Z., Ha, Y., & Li, Y. (2016). Analysis on a new data mining algorithm of the statistics work. Telkomnika, 14(3A), 42-46.
Review the information on how statistics are used in data mining.

Le, J. (2018, June 19). Decision Trees in R. Datacamp.
A great overview of Decision Trees with R.

Mahoney, M. (2019, July 15). Basic statistics (using R). Introduction to data exploration and analysis with R. Bookdown.
A great review of basic statistics in R in Chapter 14.

Weihong, G., Shenghan, G., Hui, W., Xiao, Y., Januszczak, A., & Suriano, S. (2017). A data-driven diagnostic system utilizing manufacturing data mining and analytics. SAE International Journal of Materials & Manufacturing, 10(3), 30-40.
Review the information on data mining and analytical processes.

Witten, I. H., Frank, E., & Hall, M. A. (2017). Algorithms: The basic methods. Implementations: Real machine learning schemes. Data mining: Practical machine learning tools and techniques (3rd ed., pp. 90-160).
Read Chapter 4, Algorithms: The basic methods.

Wicker, Z. T., & Browning, J. B. (2021). Central tendency, variance, and variability. In Visualizing health care statistics: A data-mining approach: Vol. Second edition (pp. 14-28). Jones & Bartlett Learning.
Chapter 2 provides great examples of basic statistics with R and Excel.

Wicker, Z. T. & Browning, J. B. (2021). Occupancy and utilization data. In Visualizing health care statistics: A data-mining approach: Vol. Second edition (pp. 55-78). Jones & Bartlett Learning.
Chapter 4 provides great examples about basic statistics with R and Excel.