Directory to a variety of statistical procedures

Statistical Procedure Type of Data Analyzed Null Hypothesis Tested

One-Sample Tests

Chi-square test of Goodness of Fit. Categorical (nominal-level). Cases are distributed over categories according theory.
Student t test--One Sample. Interval (continuous). The sample is drawn from a population having a specific mean.

Two Independent-Samples Tests

Wilcoxon Independent Samples Test Ordinal (rank-ordered) data. The two samples are drawn from the same population (the median values of the two samples are identical).
Chi-square Test of Equality of of Distributions (Independence) Categorical (nominal-level) This is typically use with cross-tablulated data (i.e. for frequency data than can be cast in  two-fold or rows x columns table. The null hypotheses is that the row variable is independent of the column variable.
Mann-Whitney U Test Ordinal (rank-ordered) data. The two samples are drawn from the same population (the median values of the two samples are identical).
Student t Test for Independent Samples Interval (continuous) data collected from two independent groups. The two samples are drawn from a common population (they have the same mean).

Two Dependent-Samples Tests

Wilcoxon matched pairs signed ranks test Ordinal or interval (ordered metric scale) {A very powerful test, especially for small samples}
 
The medium difference (d = x - y) between members of pairs is zero.
McNemar's Test for Matched Pairs Categorical (nominal-level) The number of "A followed by B" pairs is equal to the number of "B followed by A" pairs.
 
Friedman Two-way ANOVA by Ranks Ordinal (rank-ordered) data, usually ratings of several judges. The ratings of several judges are not related.
 
Sign Test Two sets of ordinal (rank-ordered) data collected on the the same individuals or pairs. The median scores under the two conditions are identical.
Student t test for dependent samples Interval (continuous), for either a repeated measures or matched-pairs design. The mean scores for the two (repeated or paired) observations are identical.
     

Tests of Relationships (Correlations)

Spearman correlation coefficient Ordinal No monotonic relationship between the variables.
Pearson correlation Interval No linear relationship between the variables
Comparing two correlation coefficients Interval for raw data otherwise ordinal or interval Two correlations are equal (in strength).
     

Effect Size Calculators

     
     
     
     
 


STATISTICAL TOOLS AND CALCULATORS

TOP PICKS

A Really Nice Chi Square Calculator Another Chi Square Calculator
Probabilities for Several Statistical Distributions Probability values for z, t, and P2
Probability Distribution Functions Daniel Soper's Effect size calculator for multiple regression.
Confidence interval for proportions Dr. Lee Becker's Effect size calculator
Free Statistical Software (a collection on the web) A downloadable Effect Size calculator
More Free Statistical Software Principal components and Factor Analysis
A variety of statistical calculators and statistical applets.
More statististical calculators and applets (from the Chinese University of Hong Cong)
Statistics on the Web (A great source for finding online statistical resources)
Another source for statistical calculators (From Daniel Soper)
Calculator for confidence intervals of odds ratio in an unmatched case control study.

ADDITIONAL RESOURCES FOR STATISTICS

Links to a variety of statistical resources A Variety of Statistical Tools
Visual Statistic System Visual Labs in Prob. and Stats.
Social Research Methods
Free Stuff to Help in Learning Statistics StatSoft
Practical Statistics (A collection) StatCrunch (You need to register for this one)
Meta-Analysis Procedures & Calculators IFA Statistical Procedures
Stat Pages.net (A variety of statistical procedures available on the web). UCLA Technology Services: Logistic Regression

POWER ANALYSIS SOFTWARE

g*Power Power analysis software from the Institut fur Experimentelle Psychologie, University of Dusseldorf. Power Analysis. Java applets for power and sample size