Data Analytics for Experts

Data scientists often encounter non-conforming data when analyzing multiple groups and when tracking the same group over various periods. It's also expected to have insufficient data for analysis. In such cases, data analysis techniques should focus on statistical science related to "dependent" samples and "non-parametric" tests as alternatives to parametric ones (Data Analysis for Professionals). Determining the sample size is a common question when designing an analytical project. Should we consider the Big Data solution where all the data is included? This course will address these questions, discussing their advantages and disadvantages.

Workshop Overview

Learning Outcomes

Compare dependent samples with independent ones.
Compare non-parametric analytics with parametric ones.
Face the two types of errors in statistical tests with « power analysis.
Calculate sample size with scientific methods.
Understand factors that influence sample size.
Explore the different errors while defining sample size.
Manipulate multiple software solutions with the correct interpretation of results.