Data management, description and analysis

In this course, you will learn the basics of understanding your data and why classifying your data correctly is the first step to making good decisions. You will describe data both graphically and numerically using descriptive statistics and the R program. You will be introduced to the four probability distributions commonly used in data analysis. You will analyze data sets using the appropriate probability distribution. Finally, you will learn the basics of sampling error, sampling distributions, and decision errors. This course can be taken for credit toward CU Boulder’s Master of Science in Data Science (MS-DS) program, offered on Coursera. The MS-DS is an interdisciplinary degree that includes faculty from CU Boulder’s Applied Mathematics, Computer Science, Information Science, and other departments. The MS-DS is a learning outcomes-based, no-application program that is ideal for individuals with broad educational and/or professional experience in computer science, information science, mathematics, and statistics. Learn more about the MS-DS program at https://www.coursera.org/degrees/master-of-science-data-science-boulder.