Probability & Statistics courses

Linear regression and logistic regression are two of the most widely used statistical models. They act like master keys, unlocking the secrets hidden in your data. In this course, you’ll gain the skills you need...

Forecasting involves making predictions about the future. It is required in many situations: deciding whether to build another power generation plant in the next ten years requires forecasts of future demand; scheduling staff in a...

4.68

Conduct experiments w/computer models and understand how least squares regression is used to build an empirical model from experimental design dataUnderstand the response surface methodology strategy to conduct experiments where system optimization i...

4.54

This course introduces students to data and statistics. By the end of the course, students should be able to interpret descriptive statistics, causal analyses and visualizations to draw meaningful insights. The course first introduces a...

Do you want to take your probability skills to the next level? This course will help get you there, using problem-based learning with probability puzzles as the framework. As you are guided through their solutions,...

4.69

We have all heard the phrase “correlation does not equal causation. ” What, then, does equal causation? This course aims to answer that question and more! Over a period of 5 weeks, you will learn...

4.29

Power and Sample Size for Longitudinal and Multilevel Study Designs, a five-week, fully online course covers innovative, research-based power and sample size methods, and software for multilevel and longitudinal studies. The power and sample size...

Hypothesis testing lets you ask questions about your datasets and answer them in a statistically rigorous way. In this course you'll learn how and when to use common tests like t-tests, proportion tests, and chi-square...

Clinical trials are scientific experiments that are conducted to assess whether treatments are effective and safe. They are used by a variety of organizations, including pharmaceutical companies for drug development. Biostatisticians play a key rol...

4.77

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 the results of your analysis in a...

4.14

Explain the three basic methods of Econometrics. Apply different econometrics models to examples of daily life. Interpret and carry out several basic analysis strategies (correlation, regression and distribution. Ask relevant questions that can...

Statistical Modeling in R is a multi-part course designed to get you up to speed with the most important and powerful methodologies in statistics. In this intermediate course 2, we'll take a look at effect...

The world is full of unobservable variables that can't be directly measured. You might be interested in a construct such as math ability, personality traits, or workplace climate. When investigating constructs like these, it's critically...

4.66

This course will provide a set of foundational statistical modeling tools for data science. In particular, students will be introduced to methods, theory, and applications of linear statistical models, covering the topics of parameter estimation,...

4.84

We are always using experiments to improve our lives, our community, and our work. Are you doing it efficiently? Or are you (incorrectly) changing one thing at a time and hoping for the best? In...

Everything happens somewhere, and increasingly the place where all these things happen is being recorded in a database. There is some truth behind the oft-repeated statement that 80% of data have a spatial component. So...

Experimental design is a crucial part of data analysis in any field, whether you work in business, health or tech. If you want to use data to answer a question, you need to design an...

From stock prices to climate data, time series data are found in a wide variety of domains, and being able to effectively work with such data is an increasingly important skill for data scientists. This...

Linear regression and logistic regression are the two most widely used statistical models and act like master keys, unlocking the secrets hidden in datasets. This course builds on the skills you gained in "Introduction to...

Now that you're familiar with the basics of network analysis it's time to see how to apply those concepts to large real-world data sets. You'll work through three different case studies, each building on your...