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Statistical Theory
Last updated on February 21, 2012

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

  1. Wiggins R. L. (2010). Statistical Theory. General Books LLC, Memphis.

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