This course presents the fundamentals of inference in a practical approach for getting things done. After taking this course, students will understand the broad directions of statistical …

This course covers commonly used statistical inference methods for numerical and categorical data. You will learn how to set up and perform hypothesis tests, interpret p-values, and report …

This course aims to help you to draw better statistical inferences from empirical research. First, we will discuss how to correctly interpret p-values, effect sizes, confidence intervals, Bayes …

This specialization can be taken for academic credit as part of CU Boulder’s Master of Science in Data Science (MS-DS) degree offered on the Coursera platform.

Statistical inference courses can help you learn hypothesis testing, confidence intervals, regression analysis, and data interpretation. Compare course options to find what fits your …

Statistical Inference and Hypothesis Testing in Data Science Applications This course is part of Data Science Foundations: Statistical Inference Specialization

This course introduces statistical inference, sampling distributions, and confidence intervals. Students will learn how to define and construct good estimators, method of moments …

This course covers commonly used statistical inference methods for numerical and categorical data. You will learn how to set up and perform hypothesis tests, interpret p-values, and report …

You’ll be introduced to inference methods and some of the research questions we’ll discuss in the course, as well as an overall framework for making decisions using data, considerations for …

This specialization provides a comprehensive understanding of advanced statistical techniques used in data science. Learners will explore linear regression, model diagnostics, variable …