- Parametric statistical methods
- Non-parametric statistical methods

Parametric and non-parametric statistical methods

- Supervised statistical learning
- Unsupervised statistical learning
- Time series learning
- Semi-Supervised learning

Types of statistical learning

Statistical learning involves using supervised tools, unsupervised tools, time series learning, and semi-supervised tools and methods to analyze data to understand the data, extract knowledge, and infer insights.

University of Michigan - Ann Arbor

The marriage of Statistics, Computer Science, and Domin knowledge built Data Science.

Data science is interdisciplinary

Dhar, V. (2013). Data science and prediction. Communications of the ACM, 56(12), 64-73.

Data science and prediction

James, G., Witten, D., Hastie, T., & Tibshirani, R. (2013). An introduction to statistical learning (Vol. 112, pp. 3-7). New York: springer.

An Introduction to Statistical Learning with Applications in R

Hastie, T., Tibshirani, R., & Friedman, J. (2009). The elements of statistical learning: data mining, inference, and prediction. Springer Science & Business Media.

The Elements of Statistical Learning: Data Mining, Inference and Prediction

Statistical learning

There are two types of research methods: 

- Quantitative research
- Qualitative research

Both quantitative and qualitative types of research are required and often complement each other.  Science became more dependent on quantitative data and conduct quantitative tests and use qualitatively described relations.


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