XLSTAT



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The XLSTAT statistical analysis add-in offers a wide variety of functions to enhance the analytical capabilities of Microsoft Excel, making it the ideal tool for your. XLSTAT Basic, essential data analysis tools for Excel The Basic solution is a competitively-priced starter solution that includes over 100 essential statistical tools that will allow you to gain deep insight into your data. You’ll benefit from data preparation and visualization tools, parametric and nonparametric tests, modeling methods. UNDERSTANDING ANALYSIS OF COVARIANCE (ANCOVA) In general, research is conducted for the purpose of explaining the effects of the independent variable on the dependent variable, and the purpose of research design is to provide a structure.

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XLSTAT-Premium is the most comprehensive XLSTAT-solution available. The software contains all the features of every solution available (does not include the optional modules!).With over 200 different statistcal features and tools, XLSTAT-Premium can be used to prepare data, visualize, explore, analyze, take decisions, predict. Take advantage of all of that data analysis tools offer today in one powerful yet user-friendly software that will reveal everything your data has to say in just a few clicks.

This solution contains every other XLSTAT-solution - this does not include the optional modules of XLSTAT!

XLSTAT-PREMIUM

XLSTAT is a data analysis system and statistical software for Microsoft Excel. XLSTAT extends Excel to an efficient and easily accessible statistics tool that covers most of the functions needed for the analysis and modeling of data. The software automatically integrates itself into your MS Excel user interface and is always addressable from there. In more than 100 countries, beyond 25.000 engineers, statisticians, consultants and scientists are already using XLSTAT and confirm the quality of the safe, efficient, easy-to-use and at the same time most reasonably priced software.

XLSTAT make use of Excel's functionality in respect to data collection and presentation of results. However, all calculations are carried out in autonomous programs. The disposal of Excel as an interface makes the product very easy to use and effective. The quality of the calculations themselves is equivalent to that of the leading scientific packages. XLSTAT comprises the complete statistics and provides routines for dose-response curves as well as for mulitvariate statistics or PLS.

XLSTAT-Premium - Overview

With XLSTAT-Premium you get all the functions of all the solutions from XLSTAT! (not including the optional modules) This gives you access to any method, any time. Prepare data, visualize, explore, analyze, take decisions, predict. Take advantage of all of that data analysis tools offer today in one powerful yet user-friendly software that will reveal everything your data has to say in just a few clicks.

Principal Component Analysis in XLSTAT

PLSPM chart in XLSTAT

Xlstat Ahc

Logistic regression in XLSTAT

XLSTAT

Survival distribution function in XLSTAT

Differential expression

Descriptive analysis - partial autocorrelogram

Tornado Plot

Dialog box for SPC functions

User's of prior versions of XLSTAT will find the following old modules in XLSTAT-Base:

  • XLSTAT-Pro
    Software for statistical functions and data analysis in MS excel.
  • XLSTAT-Pivot: a must have complement for XLSTAT users who need to quickly create pivot tables while discovering important trends and factors impacting their business.
  • XLSTAT-PLS: for Partial Least Squares Regression and PCR regression.
  • XLSTAT-ADA: for Advanced Data Analysis (RDA, CCA, GPA, MFA)
  • XLSTAT-Dose: for dose effects analysis.
  • XLSTAT-Life: for survival data analysis (Life tables and Kaplan-Meier analysis,Cox regression, ROC curves, sensitivity and specificity analysis).
  • XLSTAT-MX: for Preference mapping, GPA, penalty analysis.
  • XLSTAT-Conjoint: Conjoint analysis for marketers.
  • XLSTAT-PLSPM: for PLS Path modeling.
  • XLSTAT-Sim: for Monte Carlo simulations and risk analysis.
  • XLSTAT-SPC: for statistical Process Control and Six Sigma.
  • XLSTAT-Time: for time series analysis and forecasting (Smoothing, variable transformations, descriptive statistics, ARIMA models).

XLSTAT grows with you - optional Modules

Software needs to fit to the user - not backwards! This is why XLSTAT's functions can be extended by optional modules. These modules are for very specific applications. The optional modules of XLSTAT can be bought seperately and are not contained in any of the solutions! The optional modules will fit into your excel interface as usual and can be addressed from there anytime. Let XLSTAT adapt to your requirements!

Optional Modules

XLSTAT-3DPlot

XLSTAT-3DPlot is an excellent extension for the data visualisation with XLSTAT! More Details

XLSTAT-CCR

XLSTAT-CCR supports regression analysis with many correlated predictors. More Details

XLSTAT-LatentClass

XLSTAT-LC is a powerful tool for Latent Class Regression models and Latent Class Cluster models. More Details

Further Information

Xlstat License Key

Systemrequirements for the software XLSTAT

Windows®Mac
Further RequirementsMicrosoft Excel 2003, 2007, 2010, 2013, 2016Microsoft Excel 2011
Operating SystemWindows XP, Vista, 7, 8, 10 (32-/64-Bit)OS X
Minimum CPU800 MHz800 MHz
Min. RAM128 MB128 MB
Disk Space150 MB150 MB

Functions and solutions contained in XLSTAT-Premium

Features in XLSTAT-Base

Analyzes

  • Factor analysis
  • Principal component analysis (PCA)
  • Discriminant
  • Correspondence Analysis
  • Multiple Korrespondenzanalysev
  • Multidimensional scaling (MDS)
  • k-means clustering
  • Agglomerative hierarchical clustering
  • Gaussian Mixture Model
  • Univariate partitioning
  • Association Rules
    Using association rules can directional relations between one or more objects of a set and another set of objects are determined in a large data set.

Modeling

  • Probability Distributions
    • Beta
    • Binomial
    • Negative Binomial
    • Chi-square
    • Exponentially
    • Fisher
    • Fisher-Tippett
    • Gamma
    • GEV
    • Gumbel
    • Lognormal
    • Normal
    • Pareto
    • Poisson
    • Student
    • Uniforme
    • Weibull distribution
  • Linear regression
  • Analysis of variance (ANOVA)
  • Welch and Brown-Forsythe one-way ANOVA
  • Covariance (ANCOVA)
  • Repeated Measures Analysis of Variance (ANOVA)
  • Mixed models and Repeated Measures ANOVA
  • Binary and Multinomial Logistic Regression (Lobit, Probit, ...)
  • Ordinal logit model
  • Log-linear regression (Poisson regression)
  • Quantile
  • Cupic spline
  • Kernel regression
  • Nonlinear regression (GENFIT)
  • Two-Stage Least Squares Regression
  • Classification and regression trees
  • K Neares Neighbors (KNN)

How To Use Xlstat

XLSTATXLSTAT

Tests

Correlation and Association tests
  • Correlation test
  • Test on contingency tables
  • RV Coefficient
  • Cochran-Armitage trend test
  • Mantel test
Parametric tests
  • Comparison of k proportions
  • Comparison of one proportion
  • Comparison of two proportions
  • Equivalence test (TOST)
  • One-sample variance test
  • Comparison of variances of two samples
  • Comparison of variances k samples
  • Multidimensional tests
  • Multinomieller fit test
  • t and z tests for one sample
  • t and z for two samples
Nonparametric tests
  • Comparison of two independent samples (Kolmogorov-Smirnov, Mann-Whitney)
  • Comparison of two paired samples (Wilcoxon sign test, sign test)
  • Comparison of k independent samples (Kruskal-Wallis test)
  • Comparison of k related samples (Friedman test)
  • Mood test (median test)
  • Durbin-Skilling-Mack test
  • Page Test
  • Cochran's Q test
  • McNemar's test
  • Cochran-Mantel-Haenszel test
  • Running tests on a sample
Outlier Tests
  • Grubbs test for outliers
  • Dixon test for outliers
  • Cochran C test for variances ourlying
  • Mandel's h and l statistics for outliers
XLSTAT

Tools

  • Export as GIF, JPG, PNG, TIF
  • Data Flagger
  • MinMax Search
  • Distance of text values in a selection
  • Configuring the menu bar (hide, show, etc.)
  • Configuring Workbooks

Features in XLSTAT-Sensory

  • Preference Mapping
  • Internal preference mapping
  • Panel Analysis
  • product characterization
  • CATA data analysis
  • Sensoric Durability Analysis
    the sensorial durability analysis is used to the ideal period for the consumption of any product to be determined.
  • Generalized Bradley-Terry model
  • Penalty analysis
  • Procrustes analysis
  • Multiple Factor Analysis (MFA)
  • Semantic Differential Chart
    this method is used to analyze how several estimators evaluate the product taking into account several criteria.
  • TURF analysis
  • Experimental designs for sensory data analysis
  • Sensory Discrimination tests
  • allows you to determine to what extent a product of a second product is different.

Features in XLSTAT-Psy

  • PLS methods
  • Generalized structure component analysis (GSCA)
  • Generalized Regularized Canonical Correlation Analysis (GRCCA)
  • Canonical Correlation Analysis
  • Canonical Correspondence Analysis
  • Procrustes analysis
  • Multiple Factor Analysis (MFA)
  • Principal component analysis (PCA)
  • Redundancy analysis (RDA)

Features in XLSTAT-Marketing

  • Monte Carlo
  • Latin hypercubes
  • Preference Mapping
  • Internal preference mapping
  • Panel Analysis
  • Product Characterization
  • CATA data analysis
  • Sensorial Durability Analysis
    the sensorial durability analysis is used to the ideal period for the consumption of any product to be determined.
  • Generalized Bradley-Terry model
  • Penalty analysis
  • Procrustes analysis
  • Multiple Factor Analysis (MFA)
  • Semantic Differential Chart
    this method is used to analyze how several estimators evaluate the product taking into account several criteria.
  • TURF Analysis
  • Experimental designs for sensory data analysis
  • Sensory Discrimination tests
    allows you to determine to what extent a product of a second product is different.
  • PLS methods
  • Generalized structure component analysis (GSCA)
  • Generalized Regularized Canonical Correlation Analysis (GRCCA)
  • Canonical Correlation Analysis
  • Canonical Correspondence Analysis
  • Procrustes analysis
  • Multiple Factor Analysis (MFA)
  • Principal component analysis (PCA)
  • Redundancy analysis (RDA)

Features in XLSTAT-Ecology

  • Dose-effect analysis
  • 4-5 Parallel Lines Regression Logistic
  • Cox Proportional Hazards Models
  • Weibull Models
  • cumulative incidence
  • Kaplan-Meier analysis
  • Life Table Analysis
  • Method Comparison
    • Analysis of repeatability and reproducibility
    • Paired t-test
    • Scatterplot
    • Bias
    • Bland Altman
    • Histograms and box plot
    • Difference Plot
  • Nelson-Aalen analysis
  • ROC curves
  • Parametric survival curves
  • Detailed sensitivity and specificity analysis
  • Passing and Bablok regression
  • Deming regression

Xlstat Student

  • Parametric tests
  • Non-Parametric tests
  • Student t-test
  • ANOVA
  • Mann-Whitney
  • Kruskal-Wallis
  • Benjamini-Hochberg
  • Benjamini-Yekutieli
  • Bonferroni
  • Volcano plots
  • Heat maps
  • Canonical Correlation Analysis
  • Canonical Correspondence Analysis
  • Procrustes analysis
  • Multiple Factor Analysis (MFA)
  • Principal component analysis (HKDA)
  • Redundancy analysis (RDA)

Features in XLSTAT-Biomed

  • Dose-effect analysis
  • 4-5 Parallel Lines Regression Logistic
  • Cox Proportional Hazards Models
  • Weibull Models
  • cumulative incidence
  • Kaplan-Meier analysis
  • Life Table Analysis
  • Method Comparison
    Analysis of repeatability and reproducibility
    • Paired t-test
    • Scatterplot
    • Bias
    • Bland Altman
    • Histograms and box plot
    • Difference Plot
  • Nelson-Aalen analysis
  • ROC curves
  • Parametric survival curves
  • Detailed sensitivity and specificity analysis
  • Passing and Bablok regression
  • Deming regression
  • Parametric tests
  • Non-Parametric tests
  • Student t-test
  • ANOVA
  • Mann-Whitney
  • Kruskal-Wallis
  • Benjamini-Hochberg
  • Benjamini-Yekutieli
  • Bonferroni
  • Volcano plots
  • Heat maps
  • Canonical Correlation Analysis
  • Canonical Correspondence Analysis
  • Procrustes analysis
  • Multiple Factor Analysis (MFA)
  • Principal component analysis (HKDA)
  • Redundancy analysis (RDA)

Functions in XLSTAT-Forecast

Xlstat Version D'essai

  • Descriptive statistics
    • Autocovariances
    • Autocorrelations
    • Partial Autocorrelations
    • Cross-Correlations
    • Normal distribution
    • White-Noise tests
  • Mann-Kendall trend test
  • Homogeneity test
  • Durbin-Watson test
  • Cochrane-Orcutt Model
  • Tests on heteroskedasticity
  • Unit root and stationarity
  • Cointegration tests
  • Time series transformations
  • Smoothing Methods for Time Series
  • ARIMA
  • Spectral analysis
  • Fourier Transforms

Features in XLSTAT-Quality

  • Subgroup charts
    Use this tool to monitor production quality if you come with a group of measurements for each measurement point in the form of continuous variables. In particular they may monitor the mean and variability of the measured production quality.
  • X-cross
  • R
  • S
  • S'²
  • Attribute charts
    Use this tool to monitor production quality if you have a measurement for each measurement point in the form of categorical variables or their sums. You can monitor the particular categorical variables of the production quality of the process.
  • P Chart
  • NP Chart
  • C Chart
  • U-Chart
  • Individual charts
    Use this tool to monitor production quality if you have a measurement for each measurement point in the form of continuous variables. In particular they may monitor the moving average or median and its variability.
  • X-Individual
  • MR Moving area
  • Individual charts
    Use this tool to monitor production quality if you each have a measurement for each measurement point in the form of continuous variables. In particular they may monitor the moving average or median and its variability.
  • CUSUM or CUSUM individual
  • UWMA or individual UWMA
  • EWMA or EWMA individual

Experimental designs

Xlstat.com

  • Pareto charts
  • Gage Repeatability and Reproducibility
  • Gage Repeatability and Reproducibility for Attributes
    • Factor Effect Plans
    • Effect surfaces Plans
    • Mixture experimental designs