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 exploratory statistics, Mar. 15, 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 exploratory 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. Exploratory statistics allow to summarize information contained in datasets of various volumes using dimension-reduction and segmentation features. This Webinar presents popular exploratory statistical features with applications using the XLSTAT statistical software.
Basic knowledge in descriptive statistics (mean, median, scatter plots...)
- A few definitions: exploratory statistics, data mining, variable, individual
- Reminder: describing two quantitative variables using a scatter plot
- Expanding description on multivariate data: exploration and segmentation
- Reducing dimensions with Principal Component Analysis (PCA)
- Data segmentation with Agglomerative Hierarchical Clustering (AHC)
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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