Statistical Methods and Data Analysis

Welcome to the Statistical Methods and Data Analysis course! This course serves as an introduction to the statistical and computation methods that have become indispensable tools for those pursuing careers in public policy. Alongside offering the necessary background in basic and applied statistics, the course will also introduce you to the powerful R programming interface. For statistical methods, the course focuses on understanding and application of different concepts and tools of statistics. You will be introduced to data visualization, which is an indispensable tool in this period of vast information around us. In this course, you will learn how to summarize data using descriptive statistics. Next, you will learn about sampling and how to make inferences about the population from a sample via probability theory. You will understand the difference between experimental and observational data. You will learn how to analyze experimental data using tests of significance. For observational data, you will learn correlation analysis and regression analysis. Finally, the course will help you to learn about regression with big data. For programming skills, you will learn R as a programming language for statistical computing. R is a free software environment for statistical computing and has lots of support information available on the Internet. At the end of this course, you will have the confidence of executing your research project using R

• Explain basic statistical reasoning in data analysis
• Illustrate data analysis applications with published research examples
• Execute data analysis projects using R programming

• Basic computer and internet skills
• Ability to read course instructions in English and complete short exercises