Free short Webinar - Learn Data Science with XLSTAT: Exploring and Clustering data, Apr. 16, 2020
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 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.
Exploring and clustering data - 1 hour
Data analysis tools can be grouped into several categories, each category aiming at answering a certain type of question associated to a certain type of data. Exploratory statistics allow to summarize information contained in wide datasets using dimension-reduction and segmentation features. Exploratory Statistics are commonly used in Unsupervised Machine Learning. 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)
- Clustering data with Agglomerative Hierarchical Clustering (AHC)
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.