Search result for Probability and Statistics Online Courses & Certifications
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Experimental Design Basics
by Douglas C. Montgomery- 4.7
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Approx. 13 hours to complete
This is a basic course in designing experiments and analyzing the resulting data. The course objective is to learn how to plan, design and conduct experiments efficiently and effectively, and analyze the resulting data to obtain objective conclusions. Both design and statistical analysis issues are discussed. Applications from various fields will be illustrated throughout the course....
Statistical Inference
by Brian Caffo, PhD , Roger D. Peng, PhD , Jeff Leek, PhD- 4.2
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Approx. 54 hours to complete
Statistical inference is the process of drawing conclusions about populations or scientific truths from data. There are many modes of performing inference including statistical modeling, data oriented strategies and explicit use of designs and randomization in analyses. A practitioner can often be left in a debilitating maze of techniques, philosophies and nuance....
An Intuitive Introduction to Probability
by Karl Schmedders- 4.7
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Approx. 30 hours to complete
This course will provide you with a basic, intuitive and practical introduction into Probability Theory. You will be able to learn how to apply Probability Theory in different scenarios and you will earn a "toolbox" of methods to deal with uncertainty in your daily life. The course is split in 5 modules....
Data Science Fundamentals for Data Analysts
by Emma Freeman , Mark Roepke- 0.0
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Approx. 19 hours to complete
In this course we're going to guide you through the fundamental building blocks of data science, one of the fastest-growing fields in the world! With the help of our industry-leading data scientists, we’ve designed this course to build ready-to-apply data science skills in just 15 hours of learning. Welcome to the Course...
Fitting Statistical Models to Data with Python
by Brenda Gunderson , Brady T. West , Kerby Shedden- 4.4
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Approx. 15 hours to complete
In this course, we will expand our exploration of statistical inference techniques by focusing on the science and art of fitting statistical models to data. We will build on the concepts presented in the Statistical Inference course (Course 2) to emphasize the importance of connecting research questions to our data analysis methods....
Regression Models
by Brian Caffo, PhD , Roger D. Peng, PhD , Jeff Leek, PhD- 4.4
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Approx. 54 hours to complete
Linear models, as their name implies, relates an outcome to a set of predictors of interest using linear assumptions. Regression models, a subset of linear models, are the most important statistical analysis tool in a data scientist’s toolkit. This course covers regression analysis, least squares and inference using regression models. Analysis of residuals and variability will be investigated....
Data – What It Is, What We Can Do With It
by Jennifer Bachner, PhD- 4.5
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Approx. 11 hours to complete
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 framework for thinking about the various purposes of statistical analysis. We’ll talk about how analysts use data for descriptive, causal and predictive inference....
Experimentation for Improvement
by Kevin Dunn- 4.8
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Approx. 13 hours to complete
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 this course, you will learn how to plan efficient experiments - testing with many variables. You get to keep all of it, all freely downloadable....
Factorial and Fractional Factorial Designs
by Douglas C. Montgomery- 4.8
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Approx. 12 hours to complete
Many experiments in engineering, science and business involve several factors. This course is an introduction to these types of multifactor experiments. The appropriate experimental strategy for these situations is based on the factorial design, a type of experiment where factors are varied together. Unit 1: Introduction to Factorial Design Instructor Welcome...
Inferential Statistics
by Annemarie Zand Scholten , Emiel van Loon- 4.4
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Approx. 23 hours to complete
Inferential statistics are concerned with making inferences based on relations found in the sample, to relations in the population. Inferential statistics help us decide, for example, whether the differences between groups that we see in our data are strong enough to provide support for our hypothesis that group differences exist in general, in the entire population....
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