Web Pages that Perform Statistical
Calculations!
( StatPages.net )
Over 600 Links (including 380
Calculating Pages) -- And Growing!
(Updated 11/19/2007-- check out What's New, and the Awards and Recognition this site
has received.)
The web pages listed here comprise a powerful,
conveniently-accessible, multi-platform statistical software package. There are
also links to online statistics books, tutorials, downloadable software, and
related resources. All of these resources are freely accessible, once you can
get onto the Internet. FREE dial-up Internet
access is available from NetZero and Juno.
These pages are located on servers all over the world, and are the
result of much cleverness and hard work on the part of some very talented
individuals. So if you find a page useful it would be nice to send the authors a
short e-mail expressing your appreciation for their hard work and generosity in
making this software freely accessible to the world. Please let me know of any
dead links, computational errors, or other problems you might encounter (e-mail
me at johnp71@aol.com).
Table of Contents for
this page...
- Selecting the right kind of
analysis
- "Online Software" Package
websites
- Calculators, plotters,
function integrators, and interactive programming environments
- Probability distribution functions:
tables, graphs, random number generators
- Descriptive statistics,
histograms, charts
- Confidence intervals,
single-population tests
- Sample comparisons: t-tests,
ANOVAs, non-parametric comparisons
- Contingency tables, cross-tabs,
Chi-Square tests
- Regression, correlation, least
squares curve-fitting, non-parametric correlation
- Analysis of survival data
- Bayesian Methods
- Other statistical tests and
analyses
- Specialized and
discipline-specific tests and analyses
- Power, sample size and experimental
design
Other Statistical Resources...
There are a bewildering number of statistical analyses out there, and
choosing the right one for a particular set of data can be a daunting task. Here
are some web pages that can help:
- Statistical
Decision Tree, from the developers of the MicrOsiris package. This is an
interactive set of web pages to help you select the right kind of analysis to
perform on your data. It asks you a simple series of questions about your data
(how many variables, etc.), then makes recommendations about the best test to
perform.
- Choosing a
Statistical Test, Chapter 37 of Dr. Harvey Motulsky's book Intuitive
Biotatistics.
- "Selecting
Statistics", by Bill Trochim (Cornell). Another interactive set of
web pages to help you select the right kind of analysis to perform on your
data.
- The very
extensive test-selection routine used in Dr. Robert Knodt's MODSTAT
statistical package.
As you can see from looking at the StatPages.net web site, there are many
"stand-alone" web pages that are each designed to perform only a single test or
calculation. In addition, some talented individuals and groups have created
coherent website that perform an entire suite of calculations, with a
logical organization and consistent user interface. Each of these web sites is
really a fairly complete online statistical software package in itself. Here are
some of these "comprehensive" statistical analysis web sites:
- OpenEpi Version 2.2 -- OpenEpi is a
free, web-based, open source, operating-system-independent series of programs
for use in public health and medicine, providing a number of epidemiologic and
statistical tools. Version 2 (4/25/2007) has a new interface that presents
results without using pop-up windows, and has better installation methods so
that it can be run without an internet connection. Version 2.2 (2007/11/09)
lets users run the software in English, French, Spanish, or Italian.
- ProtoGenie -- a free extensible
web-based environment for research design and data collection for surveys,
experiments, clinical trials, time series, cognitive and vision research, and
methods courses. Lets you specify groups and define measurement and treatment
events and their sequencing. The goal is to let users move smoothly from
research design and data collection to interim and final statistical analysis.
- Statlets --
an "online statistical computing center" providing access to over 50 applets
in which you can enter data, compute statistics, create tables and graphs, and
print out the results. Provides basic plotting, probability distributions,
summary statistics, one-sample analysis, time-series analysis, two-sample
comparisons, regression analysis, attribute estimates, ANOVAs, and Statistical
Process Control. This public version supports up to 50 rows and 8 columns of
data. For larger data sets, a single-user copy or a corporate deployment
license can be purchased.
- The Calcugator -- a
calculator, plotting engine, and programming environment. Also available as a
free stand-alone downloadable program. Simple to use; rivals programs like
MATLAB, with 200 functions/operators to perform real, integer, rational,
complex, boolean, statistical, vector, array and matrix computations. Both the
input and output of the program are displayed on standard windows which can be
further edited, saved, merged, print-previewed and printed. Allows rapid
creation of 2D and 3D plots of functions, polar and parametric displays, bar,
pie, pareto and xy charts. All plots can be configured using the mouse
(zooming, panning, selecting). Titles and labels are supported, and all
figures created by the Calcugator can be exported into popular file formats or
pasted into an editable window. As a programming environment it has a simple
and compact language with identical syntax to Java/C/C++, and allows
user-defined functions.
- SISA (Simple Interactive
Statistical Analysis) -- SISA allows you to do statistical analysis
directly on the Internet. Click on one of the procedure names below, fill in
the form, click the button, and the analysis will take place on the spot.
Study the user friendly guides to statistical procedures to see what procedure
is appropriate for your problem.
- The WebMath page performs a large
number of numeric calculations and symbolic algebraic manipulations of the
type that might arise in high school / college algebra and calculus, including
some elementary statistical calculations. In doing so, it provides a detailed
step-by-step explanation of how it arrived at the answer.
- Expression Evaluators -- type in any numeric
expression; the computer will evaluate it and display the results...
- Scientific Calculator
(numeric expression evaluator)
- Expression
Evaluator, similar to above, but doesn't require Java or JavaScript
capability
- Visible Memory
Kalculator -- provides a growing visible memory of all values inputed or
computed for use at any time later (just click on it). Can also read text
(ascii) files.
- Evaluates
various sums, cross-products, and other "building block" expressions that
arise in statistical formulas
- The Vanderbilt MathServe
Calculus Toolkit has separate calculating/graphing pages for: Factoring
Polynomials, Partial
Fractions, Polynomial
Equations, Graphs
of Functions, Graphs
of Equations, Limits,
Derivatives,
Antiderivatives
(Indefinite Integrals), Definite
Integrals, Inverse
Functions, Newton's
Method, Polynomial
Interpolation, Sums, Parametric
Equations, and Polar
Functions
- Inverse
Symbolic Calculator -- tells you where a number came from. For example,
if you type in 1.55838744, this program will tell you that it's really
the square root of 17/7.
- Calculators -- pages that look and act like a
pocket calculator...
- Plotters -- type in any algebraic function; it
displays the graph...
- Function
plotter -- Lets you zoom in and out to view any portion of the graph.
(Needs Java.)
- Function
plotter -- Plot almost any function or relation found in high school and
undergraduate college mathematics. Plots functions of the form y = f(x),
such as y = x2 or y = 3x + 1, or relations of the form f(x,y) = g(x,y), such
as x2 + y2 = 4. (No Java needed.)
- Linear
Programming Grapher-- Enter a linear function of two variables to be
minimized, and any number of linear inequality expressions, and the page
will instantly solve it and display a graph showing the feasible region and
the constraints.
- Simplex
Tool -- Similar to the Linear Programming Grapher, but works with
functions of more than two variables, and doesn't graph the results.
- Integrators -- type in any function; the computer
displays the indefinite integral function (if one exists) and/or the value of
the definite integral (area under the curve) between two endpoints...
- Interactive Programming Environments -- These pages
implement various mathematical programming languages. You can enter commands
or entire programs (type or copy/paste) into the web page, and they will be
executed immediately.
- Rweb -- an interactive
web-based interface to the "R" statistical programming language (similar to
S or S-plus)
- SHAZAM -- a programming
environment for econometricians, statisticians, and others who use
statistical techniques. Its primary strength is estimating and testing many
types of regression models. Provides a flexible command language and
capabilities for programming procedures. Has an interface to the GNUPLOT
package for high quality graphics.
- Mx -- a
matrix algebra interpreter and numerical optimizer for exploration of matrix
algebra. Many built-in fit fuctions for structural equation modeling and
other statistical modeling. Has fitting fuctions like those in LISREL,
LISCOMP, EQS and CALIS, along with facilities for maximum likelihood
estimation of parameters from missing data structures, under normal theory.
Users can easily specify complex 'nonstandard' models, define their own
fit functions, and perform optimization subject to linear and nonlinear
equality or boundary constraints.
- Probability Integrals -- these pages take the place
of a handbook of statistical functions. They're arranged with the most
comprehensive,multi-function pages first...
- These pages contain calculations for a very wide assortment of
probability distribution functions, including Normal, Bivariate Normal,
Student t, Chi-Square, Fisher F, Bivariate Normal, Noncentral Student t,
Non-central Chi-Square, Non-central Fisher F, Poisson, Log-normal,
Exponential, Beta, Gamma, Logistic, Binomial, Negative Binomial,
Multinomial, Cauchy, Gumbel, Laplace, Pareto, Weibull, Uniform (continuous
and discrete), Triangular, Geometric, and Hypergeometric:
- These pages each compute probabilities for the four most common
probability distributions:
- Normal,
t, Chi-Square, and Binomial (density and cumulative) probabilities;
(When you get to the Rweb page, scroll down to the Analysis
Menu and select Probability.)
- Normal, t, F,
Chi-Square probabilities and inverses, with nice graphical
representation.
- Normal, t, F,
Chi-Square, Binomial, and Uniform probabilities and inverses
- Normal,
Student
t, Chi-Square,
and Binomial
probabilities and inverses. Provides an easy graphical way to specify
whether you want upper / lower tail or interior integrals.
- Central and
tail areas for Normal, Student, F, Chi-Square, Binomial, and Poisson
distributions
- Statistical probability
distribution functions: Normal, Student t, Chi-Square, Fisher F
- P-values
for the Popular Distributions -- Binomial , Chi-square, Exponential ,
Fisher's F, K-S: Two Samples , Poisson, Normal , Student's t, and Uniform
distributions.
- Calculate
p-value from z, t, F, r, or Chi Square; or do the reverse.
- Reverse
computations: enter p-value (and, if necessary, sample sizes and/or
d.f.); program will compute z, t, F, Chi Square, and correlation
coefficient
- These pages each compute probabilities and/or inverses for a specific
distributions:
- Normal
distribution areas, with nice graphical interpretations
- A very
attractive page for Normal distribution (and inverse), with detailed
explanations
- Normal
area (1-tailed)
- Cumulative
area under the normal curve (integral from minus infinity to z)
- Chi-Square
probabilities, and reverse, with a detailed explanation
- Chi
Square probabilities and reverse
- Chi-Square
Distribution
- Chi-Square
Distribution
- Student
t Distribution
- Student t
Distribution and its inverse (t
value from p value)
- Studentized
Range -- the probability of a studentized range being less than or
equal to value x with v d.f. from r sample
- Probabilities
for the Fisher F distribution
- Another Fisher F
distribution p-value calculator.
- Critical
Fisher F value, given the alpha level, the numerator and denominator
d.f.
- Non-central
F value (by Laubscher's square root approximation), given the
F-value, numerator and denominator d.f., and the noncentrality parameter.
- Binomial,
Poisson and Gaussian distribution probabilities
- Binomial
probability calculator
- Binomial
Approximation of the Normal Distribution
- Cumulative
frequency for the Binomial distribution
- Probabilities
for Gamma, complete Beta, and Incomplete Beta distributions
- Multinomial
Distribution
- This page contains links
to printable copies (in Adobe Acrobat PDF format) of many statistical
tables including some for which no "calculating pages" are available
- Normal
Curve
- Critical Values for: Student
t, Fisher
F, Studentized
Range Statistic and Dunnett's Test, Chi-Square,
Binomial
Test, Wilcoxon
Ranked-Sums Test, Wilcoxon
Signed Ranks Test, and Correlation
Coefficient
- Converting
r to Z
- Statistical Power of: Z
Test, t-Test
for One Sample or Two Related Samples, t-Test
for Two Independent Samples, Analysis
of Variance, and Correlation
Coefficient
- Required
Sample Size for various tests
- Random Number Generators...
- Combinatorial Objects
Server -- generates an incredible assortment of...
- Permutations and their restrictions
- Subsets or Combinations
- Permutations or Combinations of a Multiset
- Set Partitions
- Numerical Partitions and relatives
- Binary, rooted, free and other trees
- Necklaces, Lyndon words, DeBruijn Sequences
- Irreducible and Primitive Polynomials over GF(2)
- Ideals or Linear Extensions of a Poset
- Spanning Trees and other Subgraphs of a Graph
- Unlabelled Graphs
- Pentomino Puzzles, Polyominoes, n-Queens
- and other puzzles and Miscellanea
- Statiscope
-- a beautifully-implemented page for calculating and displaying a large
number of descriptive statistics from a set of numbers you enter
- WebStat (an integrated
applet) can generate summary statistics, as well as histograms, stem and leaf
plots, boxplots, dotplots, parallel coordinate plots, means plots,
scatterplots, QQ plots, and time series plots
- Descriptive
Sampling Statistics -- Enter up to 80 numbers; this page will calculate
the mean, variance, SD, CV, skewness and kurtosis.
- Descriptive
statistics (mean, SD, SEM, and CI of mean). Can enter or paste raw data,
or enter mean, SD or SEM, and N to get CI.
- Descriptive
Statistics -- Enter up to 80 values; page calculates: N, mean, variance,
SD, CV, skewness, kurtosis, SEM, median, min, max, range, 1st &
3rd quartiles, interquartile range, quartile deviation, coeff of
quartile var, and absolute deviation.
- Measuring
for Accuracy -- Given a set of observed and predicted values, this
page calculates the SD of errors, mean absolute & relative error, and
Durbin-Watson statistic.
- Arithmetic,
Geometric, and Harmonic Means -- of up to 80 values.
- Rweb
- extensive tabular and graphical descriptive summarization: mean,
quartiles, histograms, scatterplot matrices (with smoothers), QQ plots (normal
and pairwise), time series, box plots. (When you get to the Rweb page,
scroll down to the Analysis Menu and select Summary.)
- The Data
Applet provides descriptive statistics, histograms, boxplots, and
scatterplots
- A
variety of descriptive statistics and a stem and leaf display
- Detect Outliers
-- this calculator performs Grubbs' test, also called the ESD method (extreme
studentized deviate), to determine whether one of the values in the list you
enter is a signficant outlier from the rest. Also contains an excellent
discussion of what to do about outliers.
- Combine
Subgroups -- calculate the mean and SD of a combination of groups from the
N, mean and SD of each group.
- Computes
summary statistics for one variable, draws a crude histogram, and sorts a list
of values. Given pairs of values, it computes the least squares regression
line and Pearson correlation coefficient.
- Basic
descriptive statistics (mean, sum of squares, variance, standard
deviation, minimum, 25th percentile, median, 75th
percentile, and maximum for up to 500 numbers
- Empirical
Distribution Function -- from up to 42 sets of [value, frequency].
- Multinomial
Distributions -- Enter up to 12 values and their corresponding
probabilities, and this page will calculate Expected Value, Variance, Standard
Deviation, & Coefficient of Variation
- Paired
Data Sets Statistics -- Enter up to 28 sample paired data sets, and this
page will calculate means, variances, and covariance
- Histogram
-- Enter up to 80 numbers, and this page will display a histogram.
- Histogram
from a set of numbers, lets you dynamically alter the interval width and
see the effect immediately
- Histogram --
type in or upload a data set or give a URL; submit; returns a colored
histogram that you can copy from the page; also does polygons and cumulative
- Determination
and Removal of Outliers -- Given a set of numbers, this page iteratively
isolates potential outliers for removal.
- Point
Pattern Analysis -- used to describe and help analyze point patterns. It
consists of 14 different analysis routines for a variety of basic descriptive
statistics: nearest neighbor analysis, K-function, space-time Knox, Join-Count
statistics, Global Moran’s I and Geary’s c, general Getis-Ord’s G, local
K-function, and more.
- Draw a
scattergram from {x,y} data
- Draw a
3-dimensional scattergram from {x,y,z} data
- Generate a VRML file to
view 3-dimensional (x,y,z) data. To view the resulting files requires a VRML
viewer.
- Compute and plot a
Kernel Density Estimate from a set of points, using Epanechnikov,
triangular, biweight or Gaussian kernels
- Compute Poisson
change-point, that is: estimate when, in a long sequence of occurrences,
the occurrence rate underwent a sudden change
- Boxplot -- type
in or upload a data set, or give a URL; submit; returns a colored boxplot that
you can copy from the page
- Parallel
Boxplot -- type in or upload a bivariate data set with a continuous
variable and a group indicator; submit; returns a colored parallel boxplots
that you can copy from the page
- Q-Q Plot -- type in
or upload a data set, or give a URL; submit; returns a colored q-q plot that
you can copy from the page
- Plot up to 10 x,y data points
- Confidence Intervals...
- for the difference between two
means, given N, mean, SD for each group
- Exact C.I.'s for Binomial
(observed proportion) and Poisson (observed count) (also available as an
Excel spreadsheet)
- Exact and
"modified Wald" C.I.'s for observed proportion or count, with a good
explanation
- Confidence
interval around a proportion, given the population size, the sample
size, the sample percentage and the confidence level. Has interesting
animation, plus a good explanation of the concepts. A related
page has no animation, but can be printed out.
- 95% C.I. around
an observed proportion
- Bayesian
"credible" intervals around an observed proportion. Somewhat comparable
to the "classic" confidence intervals, but tend to be somewhat narrower.
- 95% or 99% C.I. for
proportions for any specified sample size and population size
- 95% C.I. around an observed
sample mean
- Confidence interval
around an observed sample SD, assuming the data are sampled from a
Normal distribution
- Percentage:
Estimation & Testing -- calculates exact binomial confidence
intervals and tests of hypothesis for population proportion, from infinite
or finite populations.
- Tolerance Intervals...
- Tolerance Intervals for the
Normal Distribution. (Don't confuse tolerance intervals with
confidence intervals!) A tolerance interval for a measured
quantity is the interval in which there is a specified likelihood that a
specified fraction of the population's values lie. This page will
calculate 1-sided and 2-sided tolerance intervals for any specified
population fraction, and for any specified level of confidence, from the
mean and standard deviation of a finite sample, under the assumption that
the population is normally distributed. These calculations are also
available in a downloadable Excel spreadsheet: tolintvl.xls .
- Single-Population Tests...
- Sign and Binomial
test -- test an observed proportion against a proposed population
proportion
- Another Sign and
Binomial test
- Mean,
SD, confidence interval, etc. for a set of values
- An excellent
One-Sample Student t Test page -- enter or paste raw data, or enter
mean, SD or SEM, and N
- One-sample
Student t test for Mean vs. a Specified Value -- for up to 80
observations, and a postulated population mean.
- Student t-test of a single
mean (vs specified value) from N, mean, SD
- Another
Student t-test of a single mean (vs specified value) from N, mean, SD
- Similar test of single
mean vs 0 (equivalent to a paired Student t) from N, mean, SD
- Test for
Asymmetry around zero -- Enter a set of numbers (usually a mix of
positive and negative numbers), and the program will apply a non-parametric
test (originally created by R. A. Fisher) of whether the numbers are
consistent with a population frequency distribution that is symmetrical
around zero (but does not necessarily have to be normal). It is a
frequentist test to work Darwin's experiment with matched pairs, and
experiments like it.
- Test for the mean
being greater than some specified value. This unusual test is Bayesian
and frequentist at the same time. The null hypothesis asserts some
value for the mean of a population of positive numbers; the alternative
hypothesis says the mean is higher than that. This test gives a Bayesian
likelihood ratio that is also an upper bound on the p-value of the
frequentist test.
- Test
observed vs. expected rates of occurrence of events, based on Poisson
distribution; also includes confidence intervals and analysis of rate-ratios
(such as Standardized Mortality Ratio, Morbidity Ratio, and Comparative
Mortality Figure)
- Similar
to above, but used to study the distribution of accidents and events at the
individual level
- Exact
confidence intervals around a rate-ratio, using Liddell's method (also
contains a number of common approximations, for comparison)
- Test
observed vs expected proportions, based on the Binomial distribution
- Binomial
Test -- whether the number of "successes" differ from what was expected
based on the number of trials and the probability of success.
- Similar
to above, but deals with the probability of a particular sample size, given
an observed 'x' number positive (or white, or car crashes) vs. an expected
'U' proportion positive
- Compatibility
of Multi-Counts -- tests whether up to 14 observed event counts (each
over the same amount of time) are consistent with a single expected event
rate.
- Runs
Test for Randomness -- Enter up to 80 numbers, and this page will
calculate a runs test to see if the numbers form a random sequence
- Testing
the Variance -- of up to 80 observations against a postulated population
variance.
- Analyze
observed proportions in samples from finite populations, based on the
Hypergeometric distribution
- Test
for Normality -- Enter up to 80 numbers, and this page will test for
normality based on the Jarque-Bera statistic
- Test
for Homogeneity of a Population -- enter form 25 to 84 values; page
provides information to test whether histogram is unimodal.
- Test
for Normality -- enter up to 42 sets of [value, frequency]; page will
calculate skewness, kurtosis, and Liliefors test for consistency with a
normal distribution.
- Test
for Uniform Distribution -- enter up to 42 sets of [value, frequency];
page will calculate the Kolmogorov-Smirnov test for consistency with a
uniform distribution.
- Testing
Poisson Process -- enter up to 14 sets of [value, frequency]; page will
calculate a Chi square test for consistency with a Poisson distribution.
- Lilliefors
Test for Exponential Distribution -- tests whether a set of observed
values are consistent with an exponential distribution.
- Chi-Square "Goodness of Fit" test for observed vs expected
counts (NOT from Contingency Tables)...
- Measurement Errors and Error Propagation...
- Student t-test (for comparing two samples)...
- a very general
Student t-test web page -- paired or unpaired, equal- or
unequal-variance, from individual observations (which can be key-entered or
copy/pasted) or summary data (N, Mean, SD or SEM). Includes explanations and
advice on carrying out this type of test.
- t-test, paired
or unpaired
- t-test, paired
or unpaired
- t-test, paired or unpaired
- t-test,
paired
- Paired
Student t Test -- on up to 42 pairs of values, along with a postulated
population mean difference.
- Testing
Two Populations -- Unpaired Student t test for up to 80 observations in
each sample. Also accepts a postulated difference between the two population
means, which can be different from 0.
- A general 2-sample
comparison calculator, for paired, unpaired, equal-variance, obtaining
its p-values from table lookup or from resampling
- Unpaired
t-test from summary data (N, mean, SD)
- Very
general t-test program for comparing measured quantities, observed counts,
and proportions between two unpaired samples; also produces risk ratio,
odds ratio, number needed to treat, and population analysis.
- ANOVA (Analysis of Variance) -- comparison of two
or more samples ...
- One-Way and Factorial ANOVA for uncorrelated
samples (extension of unpaired Student t-test to more than 2
groups)...
- One-way
ANOVA, with graphical output
- One-way ANOVA for
3 Independent Samples
- ANOVA:
Testing the Means -- One-way ANOVA for three groups, each containing
up to 40 subjects.
- One-way ANOVA for
4 Independent Samples
- One-way ANOVA from
summary data (N, mean, and SD or SEM)
- Another
1-way ANOVA from summary data
- Two-way
factorial ANOVA for 2 rows by 2 columns
- Two-way
factorial ANOVA for 2 rows by 3 columns.
- Two-Way
ANOVA Test -- for blocked designs of up to 4 groups by 6 treatments.
- Two-Way
ANOVA with Replications -- for blocked designs of up to 4 groups by 6
treatments, with up to 4 replications.
- Two-way
factorial ANOVA for 2 rows by 2 columns, from summary data (N, mean,
SD)
- ANOVA
for Condensed Data Sets -- Enter up to 10 sets of (N, mean, SD); page
calculates a one-way ANOVA.
- Very
general n-way factorial ANOVA, with interactions, means table,
interaction plots, Bonferroni post-hoc multiple comparisons, and
confidence intervals. (When you get to the Rweb page, scroll down
to the Analysis Menu and select ANOVA.)
- Repeated-Measures ANOVA for correlated samples
(extension of paired Student t-test to more than 2 matched
measurements)...
- Bartlett's
Test for Equality of Multi-variances -- for up to 14 sets of [N,
variance].
- Post-hoc
Tests -- After doing a two-way (or other) ANOVA, post -hoc tests (also
called post tests) compare individual pairs of groups. This calculator does
not perform the ANOVA calculations, but takes the output from an ANOVA
(residual means square error, degrees of freedom) performs a post-hoc test
between any pairs of cells that you select (using cell means and N's), at
whatever alpha you specify.
- Tukey
LSD (Least Significant Difference), using the standard table produced by
an ANOVA
- Scheffe
Least Significant Difference, using data from a standard ANOVA table and
the N's for the two groups being compared
- Non-parametric tests (use these when the data is
not normally distributed)...
- Sign test
for matched pairs
- Median
test for unmatched pairs
- Wilcoxon
Signed-Ranks test for matched pairs -- This page takes case-by-case
pairs of matched data
- Another
Wilcoxon Signed-Ranks test for matched pairs -- This page takes
summarized, tabulated data: how many cases had differences of +1, +2, +3,
etc., and -1, -2, -3, etc.
- Comparing
Two Random Variables -- by the Mann-Whitney U test, with up to 80
observations per sample.
- K-S
Test for Equality of Two Populations -- Given two sets of frequencies
(using the same grouping intervals), this page calculates the
Kolmogorov-Smirnov test.
- Wilcoxon
Sum-of-Ranks (Mann-Whitney) test for comparing two unmatched samples
- Kruskal-Wallis
test (non-parametric ANOVA) for 2 or more groups of unpaired data --
This page requires that you first cross-tabulate your data into a matrix,
with a row for every group and a column for every different numeric value
that any subject had; the cell of the matrix tell how many subjects (if any)
in that group had exactly that numeric value.
- Least
Significant Difference between mean ranks (post-hoc test after a
significant Kruskal-Wallis test)
- Friedman
test for comparing rankings (non-parametric)
- Two-group
ordinal comparisons to assess how probable it is that the two groups come
from a single ordering, using Wald-Wolfowitz, Randomness Test,
Mann-Whitney, and Kolmogorov-Smirnov
- Two-group
paired comparisons, using T-test, Wilcoxon, Signs test, and McNemar test
- McNemar's
test for the paired comparison of proportions (or for matched pairs of
labels)
- Comparison of proportions between two groups...
- Comparison
of Binomial proportions
- Paired
Preferences Test -- Enter the sample size, and the two percentages
(preferring A and preferring B), and this program will calculate the T score
and significance level. This page is based on a normal approximation to the
binomial distribution, and should not be used if the sample size is less
than 30.
- Sequential Analysis -- each subject's data (usually
paired comparisons) is tested as it becomes available, and a decision is made
to accept or to reject the null hypothesis or to keep testing.
- WebStat (an integrated
(Java) applet) can perform Z-tests and T-tests (one-
and two-sample) for population means, and Chi-square and Fisher-F tests for
population variances
- Chi-Square tests...
- 2-by-2 table analysis
(Chi-square, Fisher Exact Test, sensitivity, odds ratio, relative risk,
difference in proportions, number needed to treat, etc.) with confidence
intervals. Also see Andrew Mackinnon's DAG_Stat -- an
Excel spreadsheet that contains even more quantities (with confidence
intervals) that can be derived from a 2x2 table).
- EpiMax Table
Calculator -- similar to the above, but with a clearer screen layout.
- for 2-by-2
table, by Fisher Exact, and by Chi Square (with and without Yates'
correction), with a good explanation
- for 2-by-2
table
- 2-by-2
table analysis (Chi Square, Fisher Exact, difference in proportions,
risk ratio, odds ratio, theta, log-odds ratio, Poisson test)
- for
2-by-N table, where the two rows represent dichotomies like lived/died,
present/absent, yes/no. This can test for a trend in the probability of an
event when you have counts of the two categories over a set of time
intervals.
- for
table up to about 30 cells
- Chi-square
Test for Relationship -- for up to a 6-by-6 cross-tab.
- for up
to 10-by-10 tables. This page also has a section for comparing observed
with explicitly-specified frequencies.
- for
any-size table
- another
for any-size table
- another
for any-size table (When you get to the Rweb page, scroll down to
the Analysis Menu and select Two Way.)
- Exhaustive
analysis of 2-by-2 tables, with Pearson Chi-square, Likelyhood Ratio
Chi-Square, Yates Chi-square, Mantel Haenszel Chi-square, Odds Ratio, Log
Odds Ratio, Yules-Q, Yules-Y, Phi-square, Pearson correlation, and McNemar
Test
- Paired
Proportion Test -- for testing whether the proportion of subjects having
some characteristic is the same in two matched groups or in one group before
and after some intervention. (Also can test against a null hypothesis
specifying some non-zero difference.)
- Also see the Evidence-Based-Medicine (EBM) calculator in the
"Biostatistical Calculators" section of the "Other Statistical Tests and Analyses"
section of this page.
- Three-dimensional Tables (2x2x2)...
- Fisher Exact tests for contingency tables...
- Exact unconditional
homogeneity/independence tests for 2-by-2 tables
(said to be more
powerful than the Fisher exact test!)
- Test
differences between two observed proportions, based on the Binomial
distribution
- Contingency table for
sequenced categories (Ordinal by Ordinal, 5-by-5 table or less)
- Contingency
table for sequenced categories, 5-by-2 table, with exact probability
calculations
- Spearman's
correlation from cross-tabbed data with sequenced row and column
categories
- McNemar's test to
analyze a matched case-control study, with a good explanation
- McNemar's
test for paired contingency tables
- Exact Bayes
test for independence in r by c contingency tables -- Can also handle
comparison of observed-vs-expected, and observed-vs-uniform situations.
- Comparison of ratings or rankings by different
raters...
- Chi-Square
test for equality of distributions
- Chi-Square "Goodness of Fit" test for observed vs expected
counts (NOT from Contingency Tables)...
- Straight Lines and Correlation Coefficients...
- Least
squares regression line and Pearson correlation coefficient.
- Variations
on straight-line fitting, when X and Y have error
- Least squares
regression. (nice interface)
- Linear
correlation and regression (nicely designed)
- Simple
Linear Regression -- for up to 84 points, with extensive output and
residual analysis.
- Correlation
and regression calculator -- input two sets of numbers (or upload a
file); computes the means, variances, covariance, correlation coefficient
and regression coefficients; also gives a scatterplot with the two
regression lines
- The
Data Applet provides descriptive statistics, histograms, boxplots, and
scatterplots
- Least
squares straight line (also allows some simple transformations), with an
interesting tutorial on
the topic
- Least
squares straight line, also creates a high-quality Postscript graph of your
data and the fitted line
- Least
squares straight line, allows several common types of y-value weighting
(constant, proportional, or Poisson errors); also allows you to recall
recently-entered data (for a limited time)
- Scatter
Diagram and Test for Outliers -- for up to 84 points.
- Bivariate
Sampling Statistics -- calculates means, variances, and covariance for
up to 42 [x,y] measurements.
- Calculate partial
correlation coefficients rbc.a, rac.b,
rab.c from rab, rac, rbc
- WebStat (an
integrated (Java) applet) can perform simple
regression analysis
- Correlation Tests...
- Spearman's rank correlation (non-parametric)...
- Correlation
test
- Significance
level corresponding to a correlation coefficient
- Testing
the Correlation Coefficient -- enter up to 42 r values, along with a
postulated population r value.
- Minimum
significant correlation coefficient for a given sample size
- 95% Confidence
Interval around an observed correlation coefficient.
- Comparison
of two correlation coefficients
- Comparison
of two or more correlation coefficients
- Comparison
of two sets of (X,Y) data to see if they are consistent with the same
straight line (tests whether the slopes are different, and whether the
lines are vertically distinct)
- Comparing
Two Linear Regressions -- Enter two sets of [x,y] values; page
calculates two straight lines, then compares slopes and intercepts.
- Test
for Several Correlation Coefficients -- enter up to 14 sets of [N, r];
page will test whether all r's are consistent with a single population r
value.
- Biserial
and point-biserial correlation analysis
- Biserial
correlation coefficient from summary data (N, mean, SD) of the X and Y
variables
- Point-biserial
correlation analysis
- Lin's
"concordance correlation coefficient" -- first proposed by Lin
(1989) for assessment of concordance in continuous data. A breakthrough in
assessing agreement between alternative methods for continuous data. Seems
to avoid the shortcomings of correlation coefficient r, paired t-tests,
least squares analysis for slope and intercept, coefficient of variation,
intraclass correlation coefficient.. It is robust on as few as 10 pairs of
data.
- Manipulation
of a correlation matrix -- you enter the N-by-N correlation matrix, the
page computes all Partial Correlation Coefficients, all Standardized Partial
Regression Coefficients, and the Multiple Correlation Coefficient for each
variable.
- A
versatile page for calculating the significance of a correlation
(rho<>0), significance of the difference between two correlations,
power and sample size requirements for correlations testing, and the
inter-relationships between three partial correlation coefficients.
- Sobel's
test to determine the extent to which an intermediate variable
("mediator") carries the influence of an independent variable (predictor) on
a dependent variable (outcome).
- Beyond Simple 2-parameter Curve-fitting...
- Very general nonlinear
least-squares curve fitter -- almost any function you can write-- up to
8 nonlinear parameters, up to 10 independent variables.
- Another
non-linear least-squares curve fitter -- with graphical output! Choose
one of 15 pre-defined nonlinear functions of one variable and up to three
parameters.
- Compare the fit of two
models to your data. Which model fits better? Enter goodness-of-fit
(SSQ, or weighted SSQ) and # of data points and # of parameters for each
model. The calculator will compare the models using Akaike's method, , then
the F test .
- Linear,
parabolic, or cubic fit, with graphics (newer version
here)
- Multivariate
linear or univariate polynomial regression, with graphical output. Has a
good discussion of the relevant mathematics and computational accuracy.
- Fit
"rational functions" (also called "Pade functions") to {X,Y} data.
A rational function is a fraction whose numerator and denominator are
both polynomials in X. They can fit a broader range of functions than
polynomials alone can -- they can fit data where the Y value "levels off" to
a horizontal line for very large or small X, and can fit functions that have
"singularities" (Y shoots to infinity at some value of x). This curve-fitter
is part of an extensive set of online calculators to
solve problems in structural engineering (bending and buckling of beams
and plates, etc.) at the Software
for Structures web site.
- Univariate
and multiple regression, with very extensive graphical output
(histograms, scatterplots, scatterplot matrices) and residual analysis (QQ,
histogram, residuals vs dependent or predictors). Very intuitive
point-and-click interface, dynamically customized for your data. (When you
get to the Rweb page, scroll down to the Analysis Menu and
select Regression.)
- Automatic Multiple
Regression, (New Web Address!) automatically
builds a model or regression equation! You merely supply the dependent and
independent variables and it does the rest. It will find which variables are
important enough to include in the model, determine the proper
transformation of each of those variables, then look for 2-way and 3-way
interaction terms important enough to include in the model, and transform
them appropriately.
- Multiple
Linear Regression -- up to 16 data points and up to 4 independent
variables; calculates fitted model, and a large number of residual analysis
statistics.
- Quadratic
Regression -- Fits a least squares parabola to up to 84 data points, and
provides extensive residual analysis.
- Multiple regression, if you already have the correlation coefficient
matrix between all independent and dependent variables...
- Fit any of five families of
curves (linear, polynomial, exponential, descending exponential,
Gaussian) and draw a graph
- Curve fitting, smoothing,
parameter estimating, data correlating and forecasting utility
- Logistic Regression, if
the dependent variable is restricted to two values (such as whether an event
did or did not occur)
- Regression and GLM
Calculator -- performs linear, Poisson, binomial and Gamma regression,
with canonical, identity, logit, log, probit, inverse, cloglog, and sqrt
link functions
- Cox Proportional Hazards
Survival Regression Analysis
- A faster version of Cox
Proportional Hazards Analysis
- Regression
by Prevalence -- when you have data on the number of occurrences and
non-occurrences of something over a set of time intervals. Tests whether the
probability of the occurrence shows a trend over time.
- Test Bias Assessment
Program, computes statistics to help you decide if test scores predict a
criterion differently across subgroups
- Time Series Analysis...
- Autoregressive
Time Series -- tools for the identification, estimation, and forecasting
based on autoregressive order obtained from a time series.
- Detecting
Trend & Autocrrelation in Time Series -- Given a set of
numbers, this page tests for trend by Sign Test, and for autocorrelation by
Durbin-Watson test.
- Plot
of a Time Series -- generates a graph of a time series with up to 144
points.
- Seasonal
Index -- Calculates a set of seasonal index values from a set of values
forming a time series. A related page performs a Test
for Seasonality on the index values.
- Forecasting
by Smoothing -- Given a set of numbers forming a time series, this page
estimates the next number, using Moving Avg & Exponential Smoothing,
Weighted Moving Avg, and Double & Triple Exponential Smoothing.
- Runs
Test for Random Fluctuations -- in a time series.
- Test
for Stationary Time Series -- Given a set of numbers forming a time
series, this page calculates the mean & variance of the first &
second half, and calculates one-lag-apart & two-lag-apart
autocorrelations. A related page: Time
Series' Statistics calculates these statistics, and also the overall
mean & variance, and the first & second partial autocorrelations.
- Life
Table (Kaplan-Meier) -- Enter the number died and censored at each time
period, and the page calculates the cumulative survival probability and 95%
confidence intervals. Also graphs the survival curve, and exports the data, so
you can create a better graph using another program.
- Cox Proportional Hazards
Survival Regression Analysis -- specify each subject's observation time
and status (last seen alive or dead), and any number of independent variables
(predictors, confounders, and other covariates). This web page will perform a
proportional-hazards regression analysis and return the regression
coefficients, their standard errors, hazard (risk) ratio, and their confidence
intervals, and the baseline survivor curve, along with goodness-of-fit
information. You can also use a faster version by Ronald Brand
(Leiden University), or an enhanced
version by Kevin Sullivan (Emory University) that has illustrative
examples and explanatory material.
- Comparison
of Two Survival Distributions, using data from a data file in your
computer (many different file types are supported). A graph is returned to
your browser with the two survival curves plotted, along with the estimated
relative risk, standard error and p-value.
- Bayesian Credibililty
Analysis -- allows the credibility of a clinical trial finding to be
assessed in the light of current knowledge. This page takes the odds ratio and
its confidence interval from a clinical trial, and uses a newly-developed
Bayesian method to calculate a quantity called the critical odds ratio
(COR). If odds ratios at least as impressive as that indicated by the
COR can be justified by existing knowledge, then the results of the clinical
trial can be deemed credible.
- Etiologic Predictive Value (EPV)
-- a new statistical method developed for determining the probability of
symptoms being caused by a bacteriological finding, while taking carriers into
consideration. To calculate EPV, one must know the number of positive and
negative tests among patients and healthy controls as well as the sensitivity
of the test. This enables calculating the positive and negative EPV with a 95%
confidence interval.
- Exact Bayes
test for independence in r by c contingency tables -- Can also handle
comparison of observed-vs-expected, and observed-vs-uniform situations.
- Analysis of "1-degree of
freedom" data -- performs interactive frequentist and Bayesian conditional
tests for counts data having one degree of freedom. That is, it does
hypergeometric, binomial, Poisson, Bessel, and related distributions (for
double dichotomies, sign tests, a special kind of structural zero design,
etc.).
- Bayes' theorem calculations
-- takes prior probabilities and conditional probabilities, and calculates
revised probabilities. (great for solving certain kinds of brain teaser
puzzles)
- Interpret P
values -- Compute post test probability to take into account the context
of the experiment, as expressed by the prior probability that your hypothesis
is true.
- Bayesian
calculations for diagnostic tests -- computes interrelationships among
true pos, true neg, false pos, false neg, prevalence, sensitivity,
specificity, predictive values, and likelihood ratios.
- Calculate the post-test
probability of an outcome (disease) from prior probability (prevalence) of
the disease, and from the sensitivity and specificity of the test
- Sequential
Experimental Design for testing the probability ratios
- 2-by-2 table analysis
(Chi-Square, sensitivity, odds ratio, relative risk, etc. with confidence
intervals
- Wald's
Sequential Probability Ratio's -- for designing a sequential experiment in
which a decision is made after each observation either to accept the null
hypothesis, accept the alternate hypothesis, or acquire more observations.
- Universal Inventory/Test
Scorer will instantly and automatically score ANY objective test or
personality inventory/questionnaire. For any particular questionnaire, you
create a text file that describes the scores associated with each possible
answer to each question (True/False, A/B/C/D/E, Likert Scale, etc.). It is
available as a Java implementation and as JavaScript implementation. These
will run online, or can be downloaded to be run locally on your computer
(offline from the Internet).
- Interactive
Cross-Validation -- Performs the "leave-one-out" cross-validation
inference for: central tendency, least-squares lines, one-dimensional
multinomial tables, two-dimensional contingency tables with structural zeroes,
k-sample problems, and block-and-treatment designs. The web page is
well-documented, with about a dozen examples worked out and explained.
- Fittestmodel --an online forum,
on which statistical evidence can be presented that is always replicable,
testable and extendible at the 'click of a button'. The name
Fittestmodel encompasses both the goal and the means of science, namely
to find the fittestmodel by fitting, testing and modelling. Users may discuss
statistical evidence online or query for results based on search criteria such
as dataseries, methods or criteria that measure the 'quality' of results.
Publicly available datasets from various sources may be combined into new
statistical evidence and statistical techniques will be added on a continuous
basis, by user request or otherwise.
- Bonferroni
adjustment of critical p-values when performing multiple comparisons (has
an excellent discussion of this topic)
- Multiple
comparisons correction (Bonferroni adjustment)
- Number Needed to
Treat, based on a 2-by-2 table
- Detect
Outliers -- this calculator performs Grubbs' test, also called the ESD
method (extreme studentized deviate), to determine whether one of the values
in the list you enter is a signficant outlier from the rest.
- Selection Bias
Calculator for Prevalence Estimates
- Calculate and plot an ROC Curve
(for grouped predictor data)
- Clustering
Calculator generates tree structures of data clustering, and much more
- Misclassification
Bias in Prevalence Studies
- Predictive Value
from Sensitivity, Specificity and Prevalence, (when analyzing a clinical
test), with a nice explanation
- Selection Bias in
Case-control Studies
- NetMul: a
browser interface to a program that performs:
- Principal Coordinate Analysis (PCO)
- co-inertia analysis
- discriminant analysis and within- or between-class analyses
- analyses on distance matrices or neighboring graphs.
- A Web-Based SAS Code
Developer for Experimental Designs
- Simultaneous
Equations and Matrix Inversion -- up to 10 equations (or 10x10 matrix).
- Linear
Optimization with Tools for Sensitivity Regions -- This page finds the
optimal solution, and does a post-optimality analysis of small-size linear
programming problems (constrained optimization).
- Recognition
Memory Analysis -- Enter the "Hit Rate" and the "False Alarm Rate", and
the program will calculate d' (parametric discriminability), C (parametric
bias), A' (non-parametric discriminability), B''D (non-parametric
bias), Pr (high-threshold discriminability), and Br (high-threshold bias).
- Martindale's
Reference Desk - Calculators On-Line - Statistics (the grand-daddy
of all compendia of calculating web pages)
- Biostatistical Calculators:
- All-purpose Four-fold
Table Calculator: for Cohort or Case-control studies. Calculates Rx
parameters: CER, EER, ARR, RRR, NNT; Dx parameters: Sensitivity,
Specificity, LR:, LR-, Prevalence; Hyopthesis-testing parameters: RR, OR,
NNH, Chi Square.
- Evidence-Based Medicine
(EBM) calculator -- From Warren Goff's interestingly-named web site. Analyzes one
or more fourfold (2x2) tables; calculates Chi Square, CER, EER, and RR, and
parameters related to treatment (RRR, ARR, NNT, NNH, with 95% confidence
intervals), diagnosis (Sensitivity, Specificity, PPV, NPV, Prevalence, LR+,
LR-, OR, Pre-Odds, Post-Prob), and Harm (RR, OR NNH). Can also compare two
different tables.
- Number
Needed to Treat, also Normal, Student t, Chi-Square, Binomial, and
Random Digits
- Clinical
Significance Calculator -- For two groups (control and treatment), enter
the group size and incidence rate; the page will calculate absolute and
relative risk reductions, odds ratio, and number needed to treat, along with
95% confidence intervals for each result
- Compute
ECanything from EC50 (assuming a
standard "Hill-type" dose-response relationship). Very useful in
dose-response studies.
- Thorough
analysis of 2-by-2 table relevant to Predictions and Diagnostic Tests --
sensitivity, specificity, prevalence, diagnostic accuracy, PPV, post-test
probabilities, likelihood ratio tests
- Calculation
of posttest probability from Likelihood Ratio and pretest probability
- Conversion
of Sensitivity and Specificity to Likelihood Ratios
- Calculator to predict
the probability of a successful outcome to lumbar disc surgery (based on
a logistic model)
- LODS - Logistic Organ
Dysfunction System calculator
- Scoring systems for
ICU and surgical patients -- Online calculation of scores used in
general or specialized Intensive Care or Anesthesia, including:
- Adult, General scores: SAPS II, APACHE II, SOFA, MODS , ODIN, MPM (on admission ,
24 hrs, 48 hrs , MPM Over Time) , MPM
II (on
admission, 24-48-72 hrs) ,
LODS, and TRIOS
- Adult, Specialized and Surgical Intensive Care - Preoperative
evaluation: EUROSCORE, ONTARIO, Parsonnet, System 97, QMMI, MPM, POSSUM, and Portsmouth POSSUM
- Adult, Trauma scores: ISS/RTS/TRISS, and 24 h - ICU Trauma
Score
- Adult, Therapeutic intervention, nursing ICU scores: TISS
- Pediatric, General scores: PRISM, DORA, PELOD, and PIM
- Pediatric, Specialized (Neonatal, Surgical): CRIB, SNAP, SNAP-PE, SNAP II / SNAPPE
II
- Pediatric, Trauma Scores: Pediatric Trauma
Score
- Calculators for
Clinical Formulas -- A-a Gradient,
Anion Gap, Body Surface Area, Body
Mass Index, Estimated
Creatinine Clearance, Fractional Excretion of
Sodium, Heart Disease
Risk, Ingested Substance
Blood Level, Pregnancy Due
Date , Serum
Osmolality , and Weights and
Measures (converts lbs. to kgs. and F to C)
- Disparate
Impact Analysis
- Item Analysis -- for multiple
choice questionnaires
- Statistical Quality Control (SQC)
Online -- Online calculators and tutorials to perform SQC annd Statistical
Process Control (SPC). Contains:
-
- Online versions of Military & Civilian Standard Tables: MS-105E /
ANSI/ASQC Z1.4, ISO 2859 (sampling plans for attribute data), MS-414 /
ANSI/ASQC Z1.9 (sampling plans for measurement data, and MS-1235C (sampling
inspection plans for continuous production, Procedure CSP-1).
- Online Calculators for Process Capability Index (Cp), MTBF Calculator
for a system given the part (component) failure rate, and Control Charts and
Runs Rules (Switching Rules for MS-105E, Continuous Sampling CSP-1, Western
Electric Rules, and System Reliability for consecutive-type systems)
- Queuing Theory Calculator
-- a remarkably powerful web calculator that can solve a wide variety of
queueing problems: single-server, multiple-server, infinite-server, infinite
or finite waiting room, Erlang loss model, and machine interference model
(with or without spare machines). Provides detailed output in the form of
averages, standard deviations, and frequency distributions in the form of
tables and graphs.
- Single-Case
analysis tools -- an online calculator that can do a number of tests and
analyses that are especially useful in "single-case" or "single-system"
research: Time Series (handles A-B and multiple-baseline designs, and
calculates correlations and the C-statistic, with p-value), Autocorrelation,
Chi Square, Testing Significance of Difference: t-test and Mann-Whitney U,
Binomial Expansion, and Bayesian Analysis. Also contains a good overview
of single-case methods.
- Decision Making in Economics and Finance:
-
- ABC
Inventory Classification -- an analysis of a range of items, such as
finished products or customers into three "importance" categories: A, B, and
C as a basis for a control scheme. This pageconstructs an empirical
cumulative distribution function (ECDF) as a measuring tool and decision
procedure for the ABC inventory classification.
- Inventory
Control Models -- Given the costs of holding stock, placing an order,
and running short of stock, this page optimizes decision parameters (order
point, order quantity, etc.) using four models: Classical, Shortages
Permitted , Production & Consumption, Production & Consumption with
Shortages.
- Optimal
Age for Replacement -- Given yearly figures for resale value and running
costs, this page calculates the replacement optimal age and average cost.
- Single-period
Inventory Analysis -- computes the optimal inventory level over a single
cycle, from up-to-28 pairs of (number of possible item to sell, and their
associated non-zero probabilities), together with the "not sold unit batch
cost", and the "net profit of a batch sold".
- Theoretical
Expectancy Calculator -- estimates amount of workforce improvement from
implementing a valid selection procedure in an organization. Computes
institutional expectancies under three different models.
- Investment Derivative
Calculations -- A very elaborate online calculator and real-time data
retrieval system. Includes economic regression analysis.
- Black-Scholes
Calculator -- to place a value on stock options.
- Bardahl
Calculator -- to compute the reasonable working capital needs of a
corporation.
- Probabilistic Modeling:
- Bayes'
Revised Probability -- computes the posterior probabilities to "sharpen"
your uncertainties by incorporating an expert judgement's reliability matrix
with your prior probability vector. Can accommodate up to nine states of
nature.
- Decision
Making Under Uncertainty -- Enter up-to-6x6 payoff matrix of decision
alternatives (choices) by states of nature, along with a coefficient of
optimism; the page will calculate Action & Payoff for Pessimism,
Optimism, Middle-of-the-Road, Minimize Regret, and Insufficient Reason.
- Determination
of Utility Function -- Takes two monetary values and their known
utility, and calculates the utility of another amount, under two different
strategies: certain & uncertain.
- Making
Risky Decisions -- Enter up-to-6x6 payoff matrix of decision
alternatives (choices) by states of nature, along with subjective estimates
of occurrence probability for each states of nature; the page will calculate
action & payoff (expected, and for most likely event), min expected
regret , return of perfect information, value of perfect information, and
efficiency.
- Multinomial
Distributions -- for up to 36 probabilities and associated outcomes,
calculates expected value, variance, SD, and CV.
- Revising
the Mean and the Variance -- to combine subjectivity and evidence-based
estimates. Takes up to 14 pairs of means and variances; calculates combined
estimates of mean, variance, and CV.
- Subjective
Assessment of Estimates -- (relative precision as a measuring tool
for inaccuracy assessment among estimates), tests the claim that at least
one estimate is away from the parameter by more than r times (i.e., a
relative precision), where r is a subjective positive number less than one.
Takes up-to-10 sample estimates, and a subjective relative precision
(r<1); the page indicates whether at least one measurement is
unacceptable.
- Subjectivity
in Hypothesis Testing -- Takes the profit/loss measure of various
correct or incorrect conclusions regarding the hypothesis, along with
probabilities of Type I and II errors (alpha & beta), total
sampling cost, and subjective estimate of probability that null hypothesis
is true; returns the expected net profit.
Check out the large number of power and sample size
calculators at the UCLA Statistics website. Many of them are included below.
Also, check out the very general and elegant power/sample-size
calculator by Russel Lenth (U of Iowa). It handles tests of means (one or
two samples), tests of proportions (one or two samples), linear regression,
generic chi-square and Poisson tests, and an amazing variety of ANOVAs -- 1-,
2-, and 3-way; randomized complete-block; Latin and Greco-Latin squares;
1-stage, 2-stage, and factorial nested designs; crossover; split-plot;
strip-plot; and more! This calculator is implemented in Java, and can be run as
a web page, or can be downloaded
to your computer to run offline as a stand-alone application.
Here's a collection of online power calculator web pages for specific kinds
of tests:
- For one-group tests (comparing the sample to a specified
value) or for paired two-group tests...
- For designing surveys (sample size and confidence
intervals for proportions, based on sample size, with or without corrections
for finite populations:
- Calculates sample
size for given population size, confidence interval (margin of error),
confidence level, and population proportion. Also displays margin of error
for three other specified sample sizes (your choice), and sample sizes for
three other specified confidence levels.
- Compute the
sample size, given the population size, the confidence interval and the
confidence level. A related "advanced" page
also allows you to specify the postulated proportion (rather than assuming
50%).
- Find the required sample size
or statistical
power for comparing an observed proportion with a specific value
- Confidence
Interval Calculator to compute the margin of error and confidence
interval given the population size, sample size, sample percentage, and
confidence level. An animated
version is also available, which displays the calculation of the
confidence interval graphically.
- Find the sampling
error in an observed proportion
- Calculate sample size
required for a given confidence interval, or confidence interval for a given
sample size. Can handle finite populations. Downloadable program also
available.
- Another sample-size /
confidence interval calculator for proportions in finite samples
- Power vs
sample size for survey questionnaire results, with graphical output
- Sample
size or confidence interval of a proportion
- For two-group tests...
- For ANOVAs and other multi-group comparisons...
- For regressions and correlation tests...
- Power
or sample
size for comparing an observed correlation coefficient with a specified
value
- A
versatile page for calculating the significance of a correlation
(rho<>0), significance of the difference between two correlations,
power and sample size requirements for correlations testing, and the
inter-relationships between three partial correlation coefficients
- Sample-size
for multiple regression -- will tell you the minimum required sample
size for your study, given the alpha level, the number of predictors, the
anticipated effect size (as f2), and the desired statistical
power level. If you know the effect size as R2, you can calculate
f2 from R2 with this calculator.
- Power/Sample-size
for simple or multiple linear regression -- select the Linear
regression option, then click the Run Selection button.
- Beta level
for multiple regression (i.e., the Type II error rate, which is 1
minusPower), given the observed alpha level, the number of predictors, the
observed R2, and the sample size.
- Post-hoc power
for multiple regression -- calculates the observed power for your study,
given the observed alpha level, the number of predictors, the observed
R2, and the sample size.
- Power
calculations for logistic regression with a continuous exposure variable
and an additional continuous covariate or confounding variable. Also
accommodates measurement error in the exposure variable. Has graphical
output.
- Other power calculations...
- Retrospective power
analysis (after doing the test)
- Sample
Size Determination -- For several situations: ANOVA and 2-population
economic sampling, correlation with acceptable absolute precision,
estimating the mean or proportion with acceptable absolute or relative
Precision, estimating the mean or proportion from finite populations, and
testing the mean or proportion based on the Null and an Alternative.
- Power calculations for
clinical trials and scientific experiments
- Survival
Analysis -- computes power, sample size, or detectable-effect size in a
two group design with a survival outcome.
- Generic
Poisson Test -- select the Generic Poisson test option, then
click the Run Selection button.
- Exact power
for the Fisher exact test
- A large,
well-organized collection of of power and sample size calculators,
containing many of the above links
- Find sample size, power and minimal detectable difference for a:
- Links
to printable copies (in Adobe Acrobat PDF format) of many power tables
including: Z
Test, t-Test
for One Sample or Two Related Samples, t-Test
for Two Independent Samples, Analysis
of Variance, Correlation
Coefficient, and Required
Sample Size for various tests
- Wald's
Sequential Probability Ratio's -- for designing a sequential experiment in
which a decision is made after each observation either to accept the null
hypothesis, accept the alternate hypothesis, or acquire more observations.
- Experimental Design...
- WebDOE(tm) -- for
"design of experiments". Searches for I-, D- and A-optimal designs over
continuous spaces. Factors may be continuous, fixed-level, or qualitative.
The site can handle inequality and equality (e.g., mixture) constraints;
provides color plots; performs one-click, run-order-randomization; allows
design import/export interoperable with most 3rd-party analysis software;
provides OLS and BLUP fits; and includes an extensive Classical Design
Library(tm), including factorial, fractional-factorial, Box-Behnken,
central-composite, Plackett-Burman, orthogonal array, and uniform designs.
All designs may be evaluated under the I-, D-, and A-, and S-optimality
criteria, as well as for the maximum distance between nearest-neighbor pairs
of design points (maximin criterion). The My WebDOE(tm) feature allows users
to store their designs, evaluations, and fits on-line. There is no need for
user-provided candidatepoints.
- Design
and Analysis of Comparative Experiments website by Horticulture
Research International -- provides facilities for the design and
analysis of of comparative experiments for biological and agicultural
research based on a range of experimental block and treatment structures.
Constructs simple experimental designs interactively and also constructs
appropriate statistical software for the analysis of the designs. Handles
Randomised block, Split-plot, Latin and incomplete Latin square, Trojan and
incomplete Trojan square designs.
- Tables of Latin Squares
for constructing "Williams design" experiments, in which every subject
receives every treatment. These designs are balanced for first-order
carry-over (residual effects). Tables are provided for experiments ranging
from 2 to 26 treatments. Tables can also be downloaded as a text file and as an Excel spreadsheet.
- EDGAR --
generates experimental designs and randomizes the position of experimental
treatments in the design, so that the subsequent analysis of the data is
comparatively straightforward
- Gehan/Simon
Two-Stage Designs approximating the power and significance level
specified in the input.
- Find
Optimal/MiniMax Phase-II 2-stage designs, where H0: p=p0 and H1:
p=p1>p0, subject to a fixed maximum sample size, N. Finds all the designs
that satisfy Type I & II error criteria. [see Simon, Controlled Clin
Trials, 10:1-10,1989]
- Compute
boundaries for a specified alpha spending function,
compute
drift given power and bound, and
compute
probabilities,
all based upon the Lan-DeMets method. Allows
computation of boundaries at any time during the monitoring of a study. It
is valid for any normal test statistic with independent increments. The
information time is the ratio of accrued sample size to the total sample
size for normal data.
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