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Go to: General | Statistical Software

Online Statistics Instruction


Details: Mainly focuses on college-level material and provides good explanations of statistical terms, a wealth of links to other sources, and practice exercises. Also has funny cartoons and statistics jokes.
Area covered: Mean, median, mode, range, variance, standard deviation, skew, stem and leaf displays, box plots, scatterplots, simple probability, conditional probability, probability of A and B, probability of A or B, binomial distribution, standard normal distribution, converting to percentiles, areas under the curve, estimation, confidence intervals, hypothesis testing, prediction, chi squares

The Little Handbook of Statistical Practice

Details: Provides good explanations of a variety of statistical concepts, great real-life examples and good references.
Area covered: Logarithm, summary statistics, probability, normal distribution, sampling distribution of mean, confidence interval, tests of significance, contingency table, odds, sample size calculation, nonparametric statistics, simple linear regression, comparing two measurement devices, multiple regression, ANOVA, logistic regression, degrees of freedom.

Statistics at Square One

Details: Explains basic statistical concepts and introduces some statistical tests.
Area covered: Mean, standard deviation, population, sample, probability, confidence interval, type I error, type II error, power, t-test, chi-square test, exact probability test, rank score test, correlation, regression, survival analysis

Statnotes: An online textbook

Details: Focuses on advanced statistical techniques, especially multivariate analyses, introduces software for particular analyses, provides references for theoretical frameworks.
Area covered: ANOVA, ANCOVA, MANOVA/MANCOVA, factor analysis, discriminant analysis, canonical correlation, path analysis, structural equation modeling, cluster analysis, correspondence analysis, content analysis, multilevel modeling, time serial analysis, reliability, validity, significance testing

Concepts and Applications of Inferential Statistics

Details: Provides good explanations about inferential statistics and how significance tests work.
Area covered: Principles of measurement, distribution, correlation, partial correlation, rank-order correlation, probability, chi-square procedures, t-test, one-way analysis of variance for independent/correlated samples, one-way analysis of covariance for independent samples.

StatPrimer: Statistics for Public Health Practice

Details: Explains introductory and intermediate statistical concepts, provides exercises and tables to look up test statistics.
Area covered: Measurement and sampling, frequency distribution, summary statistics, probability, estimation, hypothesis testing, mean difference based on paired/independent samples, inference about a proportion, independent proportions and cross-tabulated counts, comparison of variance, ANOVA, correlation, regression, risk ratios, odd ratios.

Introductory Statistics: Concepts, Models, and Applications

Details: An online textbook which aims at developing the concept of creating mathematical models of the world. A slightly different organizational scheme: frequency polygons, models of frequency polygons, the normal curve, and the statistics.
Area covered: Measurement, frequency distributions, models of distributions, score transformation, regression models, correlation, sampling distribution, hypothesis testing, experimental design, t-test, errors in hypothesis testing, ANOVA, chi-square test of contingency tables.

Multivariate Statistics: Concepts, Models and Application

Details: An extension of Introductory Statistics: Concepts, Models and Application. Mainly focuses on multivariate statistics.
Area covered: Multiple regression, discriminant function analysis, cluster analysis, transformation of two variables.

Electronic Textbook

Details: An exciting website, introduces many state-of-art statistical techniques.
Area covered: Elementary statistical concepts, basic statistics, ANOVA/MANOVA, association rules, boosting trees, canonical analysis, CHAID (Chi-squared Automatic Interaction Detector) analysis, C & R trees, classification trees, cluster analysis, correspondence analysis, data mining techniques, discriminant analysis, distribution fitting, experimental design, factor analysis, GDA (General Discriminant Analysis), GLM (General Linear Models), GAM (Generalized Additive Models), Generalized Lineal Models, General Regression Models.

A New View of Statistics

Details: Introduces and explains statistical theories and methods from new perspectives, an extensive coverage of both basic and advanced statistics concepts.
Area covered: Effect statistics, validity and reliability, confidence interval, statistical significance, Bayesian analysis, non-parametric analysis, repeated measures with missing values, estimate sample size, boostrapping, regression, cluster analysis, errors, factor analysis etc.

Introduction to Data Collection and Analysis

Details: Introduces how to do data collection, analysis, and presentation in survey research.
Area covered: Data transformation, sampling, survey techniques, processing survey data, data summarization, and the presentation process.

DAU Tutorial Modules

Details: It consists of two tutorial modules: math refresher and probability & statistics refresher. Both refreshers have maps navigating you through the outlines.
Area covered: Basic arithmetic, exponents and logarithms, equations, series, functions, domains and ranges, intercepts, limits, graphing functions, derivatives, integrals, basic probabilities, random variables, expectations, distributions, data analysis, regression, moving averages, exponential smoothing, clustering algorithm.