Prerequisites: Graduate School of Business student.
This course examines the integration of statistical methods with artificial intelligence (AI) techniques to analyze and interpret complex data. Students will study key statistical concepts, including descriptive statistics, random variables, probability distributions, estimation, hypothesis testing, regression, correlation analysis, and model building. AI-driven approaches will be introduced for various topics. Emphasis is placed on using statistical software and AI to facilitate data analysis and address real-world problems effectively.
Outcomes: Students will gain a high-level understanding of common statistical tools used in AI and machine learning algorithms and they will be able to derive conclusions from statistical studies; Students will be able to describe data using visual and numerical summaries, analyze and interpret data effectively, perform estimation and hypothesis testing, develop and evaluate statistical models such as regression, apply statistical software for data analysis, and present statistical findings and AI results clearly and accurately.
This course examines the integration of statistical methods with artificial intelligence (AI) techniques to analyze and interpret complex data. Students will study key statistical concepts, including descriptive statistics, random variables, probability distributions, estimation, hypothesis testing, regression, correlation analysis, and model building. AI-driven approaches will be introduced for various topics. Emphasis is placed on using statistical software and AI to facilitate data analysis and address real-world problems effectively.
Outcomes: Students will gain a high-level understanding of common statistical tools used in AI and machine learning algorithms and they will be able to derive conclusions from statistical studies; Students will be able to describe data using visual and numerical summaries, analyze and interpret data effectively, perform estimation and hypothesis testing, develop and evaluate statistical models such as regression, apply statistical software for data analysis, and present statistical findings and AI results clearly and accurately.