9. Inferential Statistics

  1. Paolo Brandimarte

Published Online: 24 MAY 2011

DOI: 10.1002/9781118023525.ch9

Quantitative Methods: An Introduction for Business Management

Quantitative Methods: An Introduction for Business Management

How to Cite

Brandimarte, P. (2011) Inferential Statistics, in Quantitative Methods: An Introduction for Business Management, John Wiley & Sons, Inc., Hoboken, NJ, USA. doi: 10.1002/9781118023525.ch9

Publication History

  1. Published Online: 24 MAY 2011
  2. Published Print: 4 APR 2011

ISBN Information

Print ISBN: 9780470496343

Online ISBN: 9781118023525

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Keywords:

  • analysis of variance;
  • confidence interval;
  • hypothesis testing;
  • inferential statistics;
  • mean;
  • Monte Carlo simulation;
  • probability;
  • stochastic convergence

Summary

This chapter first covers two classical topics, confidence intervals and hypothesis testing, within the framework of the basic problem of inferential statistics: estimating the expected value of a probability distribution. Then, it considers estimating other parameters of interest, like variance, probabilities, correlation, skewness, and kurtosis, and the comparison of two populations in terms of their means. Next, the chapter describes the basics of analysis of variance (ANOVA), and Monte Carlo Simulation. It also outlines the essential concepts of stochastic convergence; they are needed for an understanding of the law of the large numbers and also provide a reader with a justification of many estimation concepts that find wide application in statistical modeling and econometrics. Further, the chapter considers a more general framework for parameter estimation, where the author discusses desirable properties of estimators, as well as general strategies to obtain them, like the method of moments and maximum likelihood.

Controlled Vocabulary Terms

analysis of variance; confidence interval; hypothesis testing; inferential statistics; mean; Monte Carlo methods; probability; stochastic processes