Introduction
- Statistical theory is the basis for the techniques in study design and data analysis.
- It covers approaches to statistical decision-making and statistics inference.
- It gives ways of comparing statistical procedures.
- Statistical theory is based on mathematical statistics.
- It is linked to probability theory, utility theory, decision theory and optimization.
- It provides a guide to comparing methods of data collection.

Major Concepts
- Basic concepts to this theory includes the interpretation of probability as describing uncertain knowledge (i.e., Bayesian probability) is central.
- Based on sampling theory, significant difference(p<0.05) between the two groups will occur in 1:20 cases of assigning participants to groups.
Application
- To explain cause-and-effect phenomena.
- To relate research with real-world event.
- To predict/forecast the real-world phenomena based on research
- Finding answers to a particular problem.
- Making conclusions about real-world event based on the problem
- Learning a lesson from the problem.
Conclusion
- Statistical theory helps to choose between actions, so that the outcome is likely to be as good as possible, in situations with uncertainty.
References
- Wiggins R. L. (2010). Statistical Theory. General Books LLC, Memphis.
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