Equipe Raisonnement Induction Statistique
Le P A C
PAC  
LesMoyennes 
LesEffectifs  LesEchantillons  LesProportions  LeB‑A‑Bayésien  LesDistributions  LePrep 
Download LePAC
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Bruno LECOUTRE Jacques POITEVINEAU
Download LePAC
[Windows]
LePAC Copy and free diffusion of LePAC are authorized.
PAC  
LesMoyennes 
LesEffectifs  LesEchantillons  LesProportions  LeB‑A‑Bayésien  LesDistributions  LePrep 
LesMoyennes  LesEffectifs  LesEchantillons  LesProportions  LeBABayésien  LesDistributions  LePrep
Experimentation, clinical trials, systematic observations...
Beyond significance tests; confidence intervals, Bayesian methods
Didactical and convivial Bayesian module, for an easy interactive use of all the procedures
Traditional and Bayesian analysis of variance
Variancecovariance analysis
Polynomial regression and discriminant analysis
Experimental designs up to 26 factors
Univariate and multivariate analyses
Repeated measures designs with equal or unequal sample sizes
Userfriendly WINDOWS program
Easy to use
Powerful design definition
Great number of options
From traditional to Bayesian inference
Frequentist inferences: null hypothesis significance tests, confidence intervals
Bayesian procedures: "noninformative" (standard) and conjugate priors
The graphical Bayesian module ('LesMoyennes'): beyond usual significance tests
Bayesian methods express by a probability distribution the incertitude about the true value of the parameter. They are wellsuited to the aim of experimental data analysis and extend the usual null hypothesis test.
Synthetic showing of results for each inference
Interactive searching for confidence and credibility intervals
Displaying conclusions about the effect magnitude
Displaying the impact of external information (prior distributions)
Download LePAC
[Windows]
Other programs
PAC  
LesMoyennes 
LesEffectifs  LesEchantillons  LesProportions  LeB‑A‑Bayésien  LesDistributions  LePrep 
PAC  LesMoyennes  LesEffectifs  LesEchantillons  LesProportions  LeBABayésien  LesDistributions  LePrep
Interactive Bayesian inferences for comparisons of means
Easy interactive use
Raw and calibrated/standardized effects
Traditional
t
and
F
tests
Confidence interval
Bayesian procedures (and also frequentist procedures) for assessing effet sizes
Predictive inferences
Exact inference about a correlation coefficient
Tests (null hypothesis ρ=0 or ρ=ρ_{0}≠0) and confidence intervals
Fiducial Bayesian procedures
Computation of Bayesian predictive probabilities
Probability to achieve a given conclusion with a specified sample size
Sample size required to achieve a given conclusion with a specified predictive probability
Includes the traditional frequentist power as a particular case
Drawing of samples and simulations of sampling distributions for descriptive and inferential statistics
Mean, difference of two means from independent groups, standard deviation
t test statistic for one mean and of the difference of two means
Confidence or fiducial Bayesian credibility limits
Parent distributions: normal, gamma (or chisquare), exponential, or uniform
Bayesian inferences about proportions
The current version is a beta version.
One proportion (binomial or negative binomial model) for a beta
prior distribution or for a mixture of beta distributions
Different parameters derived from the proportions of two independents groups
(binomial or negative binomial model) for two independent beta prior distribution
The implication index in a 2×2 table with two binary variables (multinomial
model), for a Dirichlet prior distribution
Didactical program
Allow to interactively investigate several prior distributions, and to understand the mechanisms of Bayesian inference.
Inférence about a proportion (binomial sampling)
Inference about a mean (normal sampling with known variance)
Probability and cumulative distribution functions  Probability statements (direct and reverse)
Many continuous and discrete distributions
Transformations for continuous distributions
Possibility of lower ('left') and upper ('right') truncatures.
Predictive probability prep
(Killeen's probability of replication)
of finding a samesign effect in a replication,
Predictive probability psrep
of finding a samesign and significant at onetailed level α
effect in a replication,
Predictive probability ppreprep
of finding a samesign effect with prep larger than γ
in a replication.
PAC

LesMoyennes

LesEffectifs

LesEchantillons

LesProportions

LeBABayésien

LesDistributions

LePrep
Download LePAC
[Windows]
PAC  
LesMoyennes 
LesEffectifs  LesEchantillons  LesProportions  LeB‑A‑Bayésien  LesDistributions  LePrep 