CSIS 44609 Practical Evaluation of Data

This course will introduce students to basic statistics from a data science perspective. Statistical methods are a key part of data science. The primary objective of this course is to explain how to apply various statistical methods to data science, how to avoid their misuse and to give advice on what is important and what is not. Topics include exploratory data analysis, data and sampling distributions, statistical experiments and significance testing, regression and prediction, classification, statistical machine learning, and unsupervised learning. It starts with simple statistics and then move on to statistical methods used in data science algorithms. The concepts learned in this course should help students learn the statistical techniques required to implement data evaluation in data science tasks such as data cleaning, mining, and analysis.

Credits

3