Become an operational statistician with XLSTAT-Base, SF 19-21 June 2018

Subscribe to this statistics training course illustrated with XLSTAT-Base that will be held in San Francisco (CA) in English. You will learn the basics of descriptive statistics, multivariate data analysis (PCA, CA, AHC), statistical modeling (ANOVA, regression), statistical tests (parametric and nonparametric) as well as machine learning techniques. All of those essential features will be illustrated using the XLSTAT-Base solution.

Become an operational statistician with XLSTAT-Base, 3-day training

This training goes through most commonly used data analysis methods in a wide variety of fields including research, biostatistics, marketing, sensometrics, finance and industry. The course proposes conceptual and intuitive approaches to descriptive statistics, multivariate data analysis, tests, modeling as well as machine learning. Methods are illustrated with many examples and implementations in XLSTAT-Base, including a thorough interpretation of results. Participants are also given time to practice on real data provided by the trainer. At the end of the training, participants are able to quickly find and implement appropriate statistical methods to answer their own data-related questions, using XLSTAT-Base.


Basic experience in using Microsoft Excel



  • A couple of definitions: individuals, variables, sample, population
  • Making your dataset ready for analysis

Describing data:

  • Quantitative variables: mean, standard deviation, variance, median, quartiles, Histograms, box plots, scatter plots
  • Qualitative variables: frequencies, mode, bar chart, cross tab

Exploring large data sets:

  • Reducing dimensionality: principal component analysis, correspondence analysis
  • Segmenting data: agglomerative hierarchical clustering, k-means

 Hypothesis testing

  • Defining the null hypothesis, the p-value and error risks
  • Parametric tests assumptions
  • Parametric tests vs nonparametric tests
  • One-tailed tests vs two-tailed tests

Modeling data

  • Linear regression
  • One-way ANOVA and multiple comparisons
  • Multi-way ANOVA and interaction effects

Machine learning

  • Supervised vs unsupervised learning
  • Introduction to some supervised machine learning techniques

Deploying R procedures in Excel

  • Overviewing the XLSTAT-R code infrastructure

Trainers' profiles

Jean-Paul Maalouf

Senior statistics consultant

Jean-Paul Maalouf is a senior statistics consultant working at Addinsoft since 2014. He holds a PhD in biology and has a substantial experience in teaching statistics, an activity he has been intensively practicing since 2012. His training beneficiaries include major French research institutes (INRA, CNRS, INSERM, CIRAD, several universities) as well as private companies around the world. His teaching methods rely on explaining statistical tools conceptually rather than mathematically. Statistics become very easy to understand for the users who do not necessarily have experience in mathematics and need to become operational very quickly.

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