Back

Statistics for IT Managers

95-796

Units: 6

Description

This is an introductory course in data analysis and statistical inference. Its objective is to provide individuals who aspire to enter management or policy analysis positions with the basic statistical tools for analyzing and interpreting data. For students intending to take more advanced courses in statistics and machine learning its purpose is also to ensure that you are well grounded in the fundamentals of statistics. The course is divided into three distinct modules: descriptive statistics, statistical inference, and regression analysis. The emphasis of the lectures on descriptive statistics is the calculation and interpretation of summary statistical measures and graphical methods for describing raw data. The sessions on statistical inference are designed to provide you with the background for executing and interpreting hypothesis tests and confidence intervals. The final component of the course focuses on regression analysis, a widely used statistical methodology. Throughout the course you will regularly analyze data relevant to management and policy analysis using a statistical platform developed here at CMU called ISLE.

Learning Outcomes

Its objective is to provide individuals who aspire to enter management or policy analysis positions with the basic statistical tools for analyzing and interpreting data. For students intending to take more advanced courses in statistics and machine learning its purpose is also to ensure that you are well grounded in the fundamentals of statistics. The course is divided into three distinct modules: descriptive statistics, statistical inference, and regression analysis. The emphasis of the lectures on descriptive statistics is the calculation and interpretation of summary statistical measures and graphical methods for describing raw data. The sessions on statistical inference are designed to provide you with the background for executing and interpreting hypothesis tests and confidence intervals. The final component of the course focuses on regression analysis, a widely used statistical methodology.

Prerequisites Description

none

Syllabus