Trainings & Webinars

Addinsoft organizes public (inter-company) and private (intra-company) sessions for all levels. You can register to one of our scheduled courses or contact us for a customized training course. All of our courses are available in virtual classrooms.

Free short Webinar: Introduction to statistical modeling, Nov. 30, 2017

This is an elearning free session that lasts one hour. No need to step out of your office to attend!

It includes a 45-min presentation as well as a 10-minute Q&A session.

Language

ENGLISH

LOCATION

ONLINE

Dates

From
to

hours

From
to
CET

Statistical modeling - 1 hour

Statistical tools can be grouped into several categories, each category aiming at answering a certain type of questions associated to a certain type of data. Statistical modeling allows to investigate how variables change according to other variables, and to make predictions. This webinar quickly presents the principles of statistical modeling, with demos using the XLSTAT data analysis software.

​Prerequisites

None

Program

  • What is statistical modeling?
  • Definitions: dependent and independent variables
  • Example : Linear regression
  • XLSTAT demo: Linear regression
  • Interpreting the outputs: coefficients, p-values, , etc.
  • Prediction
  • Which modeling method to choose?

TRAINER PROFILES


Jean-Paul Maalouf

Senior statistics consultant

Jean-Paul-Maalouf_XLSTAT_Trainer.png

Jean-Paul Maalouf is a senior statistics consultant who joined the Addinsoft team in 2014. He holds a PhD in biology and has extensive experience in teaching statistics, which he has been doing intensively since 2012. He has taught at the largest French research institutions (INRA, CNRS, INSERM, CIRAD, several universities), as well as at private companies around the world. His teaching methods are based on a conceptual approach and are more focused on concrete examples than on the explanation of complex mathematical formulas. The concepts are thus easily grasped by people who do not necessarily have a background in mathematics but wish to become quickly operational in the field of data analysis.

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