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 descriptive statistics, Mar 8, 2017
This is an elearning free session that lasts one hour. No need to step out of your office to attend!
The class includes a presentation as well as a 10-minute long Q&A session.
Introduction to descriptive statistics - 1 hour
Data analysis tools can be grouped into several categories, each category aiming at answering a certain type of questions associated to a certain type of data. Descriptive statistics allow to summarize information contained in datasets using simple numbers such as the mean or the standard deviation; and charts such as box plots and scatter plots. This Webinar presents descriptive statistical features with applications using the XLSTAT statistical software.
- A few definitions: descriptive statistics, variable, individual
- Describing one qualitative variable: mode, flat sorting, pie charts
- Describing the link between two qualitative variables: cross tabulation (contingency table)
- Describing one quantitative variable: mean, standard deviation, median, quartiles, box plots
- Describing the link between one quantitative variable & one qualitative variable: multiple box plots
- Describing the link between two quantitative variables: scatter plot
- 1 quantitative var. x 1 quantitative var. x 1 qualitative var.: scatter plot with colored points
Senior statistics consultant
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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