# XLSTAT Life Sciences

## A comprehensive solution for biologists, medical researchers and environmental researchers.

## XLSTAT Life Sciences, the full-featured solution for life science specialists

**Life Sciences** is a solution especially designed for researchers and practitioners of life sciences who want to apply well-known and validated methods to analyze their data and build on their research. Obtain your results in a few simple clicks without having to leave MS Excel where your data is stored. You will get to spend more time with what really matters: interpreting your results.

As a **biologist** or **medical researcher**, use Cox or Kaplan-Meier models for survival analysis, compare methods with Passing and Bablok or Bland and Altman regressions, estimate the sample size your experiment should have with power analysis. Explore your huge OMICs datasets with our differential expression and heat map features.

If you deal with **complex psychological or social data**, you will be able to explore survey data using well-known and established tools such as correspondence analysis, look for the factors that most influence psychological scores using regression, build mixed models that take into account item or respondent effects. Explore the complex relationships that may occur between latent variables such as intelligence, wellbeing and academic performance via structural equation modeling using partial least squares. Multiblock data analysis techniques are also available.

As an **ecologist**, explore the relationships between tables (Multiple Factor Analysis, Redundancy analysis…), discover species niches (Canonical Correspondence Analysis), detect proteins that are differentially expressed (OMICs data analysis) or determine EC50 ecotoxicological doses.

XLSTAT Life Science includes all of the Basic+ features in addition to methods specific to fields related to life sciences.

## Describing data

- Descriptive statistics (including Box plots and scattergrams)
- Histograms
- Reliability Analysis
- Normality tests
- Contingency table (descriptive statistics)
- Similarity/Dissimilarity matrices (correlation…)
- Multicollinearity statistics
- Quantiles estimation
- Resampled statistics
- Biserial correlation
- Variable characterization
- Pivot table

## Analyzing data

- Principal Component Analysis (PCA)
- Factorial analysis of mixed data (PCAmix)
- Correspondence Analysis (CA)
- Multiple Correspondence Analysis (MCA)
- Principal Coordinate Analysis
- Multidimensional Scaling (MDS)
- Factor analysis
- Discriminant Analysis (DA)
- Agglomerative Hierarchical Clustering (AHC)
- k-means clustering
- Univariate clustering
- Gaussian mixture models

## Modeling data

- Distribution fitting
- Linear regression
- ANOVA (Analysis of variance)
- Welch and Brown-Forsythe one-way ANOVA
- ANCOVA (Analysis of Covariance)
- Multivariate Analysis of Variance (MANOVA)
- Logistic regression (Binary, Ordinal, Multinomial, …)
- Ordinal logit model
- Log-linear regression (Poisson regression)
- Quantile regression
- Cubic splines
- Nonparametric regression (Kernel and Lowess)
- Nonlinear regression
- Partial Least Squares regression (PLS)
- PLS discriminant analysis
- Repeated measures Analysis of Variance (ANOVA)
- Mixed models
- Ordinary Least Squares regression (OLS)
- Principal Component Regression (PCR)
- Two-stage least squares regression

## Parametric tests

- Test for one proportion
- Test for two proportions
- k proportions test
- Multinomial goodness of fit test
- One-sample t-test and z-test
- Two-sample t-test and z-test
- One-sample variance test
- Two-sample comparison of variances
- k-sample comparison of variances
- Multidimensional tests (Mahalanobis, …)
- TOST (Equivalence test)

## Nonparametric tests

- One sample Wilcoxon Signed-Rank test
- Non parametric tests on two independent samples
- Non parametric tests on two paired samples
- Kruskal-Wallis test
- Friedman test
- Page test
- McNemar's test
- Cochran's Q test
- Durbin and Skillings-Mack tests
- Cochran-Mantel-Haenszel test
- One sample runs test
- Mood test (Median test)

## Power analysis

- Statistical Power for mean comparison
- Statistical Power to compare variances
- Statistical Power for proportion comparison
- Statistical Power for comparing correlations
- Statistical Power for linear regression
- Statistical Power for ANOVA / ANCOVA / Repeated measures ANOVA
- Statistical Power for logistic regression
- Statistical Power for Cox model
- Sample size for clinical trials

## Survival analysis

- Life table analysis
- Kaplan-Meier analysis
- Cox proportional hazards models
- Proportional Hazards Model with interval censored data
- Sensitivity and specificity analysis
- ROC curves
- Nelson-Aalen analysis
- Cumulative incidence
- Parametric survival regression (Weibull model)
- Parametric survival curves
- Propensity Score Matching

## XLSTAT Basic+

XLSTAT Life Sciences includes all XLSTAT Basic+ features.

View more### Tutorials for Life Sciences

- OS
- Windows

- VERSIONS
- Win7, Win8, Win10

- OS
- Mac OS X

- VERSIONS
- ≥ 10.10

XLSTAT is a leader in software for statistical analysis in MS Excel.

Since 1993, we have worked continuously to bring you and some other 100,000 users from more than 120 countries a powerful, versatile, and above all user-friendly and affordable software to meet all of your statistical needs.

Featuring over 240 standard and advanced statistical tools, XLSTAT works as a seamless add-on to MS Excel and Google Sheets (free limited version only), allowing you to easily analyze and reformat your data within Excel.XLSTAT is compatible with both Windows and Mac.

XLSTAT uses pioneering computing techniques so that you get actionable results at unbeatable speeds: parallel computing allows you to take full advantage of all your computer processors.

Today XLSTAT offers a wide variety of industry/field specific solutions designed for each and every one of you.

So make way for a statistical software that will change the way you work.