The application of statistics has become so extensive in certain areas of pure science, mathematics, business, and social science that these disciplines have developed their own specialized names. Examples of these include: Actuarial science, applied information economics, biostatistics, business statistics, chemometrics (for analysis of chemistry data), data mining (applying statistics and pattern recognition to unlock information from data), demography, econometrics, energy statistics, engineering statistics, epidemiology, geography and geographic information systems (most notably spatial analysis and image processing), psychological statistics, reliability engineering, and social statistics.

A good course in applied statistics will attempt to discuss many of the following topics, all of which can be applied to the disciplines mentioned above:

  • Examples of research problems
  • Introduction to SPSS or other statistical software package
  • Statistical significance testing
  • Preliminary data screening
  • Comparing group means using the independent samples t test
  • One-way between-subjects analysis of variance
  • Bivariate pearson correlation
  • Alternative correlation coefficients
  • Bivariate regression
  • Adding a third variable: preliminary exploratory analyses
  • Multiple regression with two predictor variables
  • Dummy predictor variables and interaction terms in multiple regression
  • Factorial analysis of variance
  • Multiple regression with more than two predictors
  • Analysis of covariance
  • Discriminant analysis
  • Multivariate analysis of variance
  • Principal components and factor analysis
  • Reliability, validity, and multiple-item scales
  • Analysis of repeated measures
  • Binary logistic regression

The highest quality free resource for students wanting to learn applied statistics is MIT Open Courseware. A large number of books on applied statistics are available from Google Books and A great website for applied statistics is offered by StatSoft. Many tutorials are also available to students, including those from SAS, Stat Trek, Andrew Moore, and Experiment-Resources. For students interested in this subject, the Journal of Applied Statistics and The Annals of Applied Statistics should be used to stay up-to-date.

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