Mar 28, 2024  
Undergraduate Catalog 2022-2023 
    
Undergraduate Catalog 2022-2023 [ARCHIVED CATALOG]

CILS 3111 - Applied Statistics for Data Science


Credits: 3

Introduction to intermediate level applied statistics and techniques of statistical modeling. The course will utilize available primary and secondary data sets in improving the conceptual understanding. The course will involve use of programming through scripting language (Python) and statistical package R and STATA. The focus of the course will be on using understanding the following concepts by analyzing data in Python, R and STATA: inferential statistics, data mining, visualization, linear regression, decision trees, logistics regression, k-means clustering, hierarchical clustering, collaborative filtering, random forests, resampling methods, classification, singular value decomposition, regularization, choosing models and fitting parameters, generalized linear models etc.

Prerequisite(s): MATH 1113  and CILS 1130  /CISM 1130  or CSCI 1130  and BUSA 2182  or SOCI 2101  or MATH 1401  
Equivalent
CISM 3111  DATA 3111