Inferential Statistics




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E.g., 2017-06-15
E.g., 2017-06-15
E.g., 2017-06-15
Self Paced

Use R to learn the fundamental statistical topic of basic inferential statistics. In the second part of a two part course, we’ll learn how to take data and use it to make reasonable and useful conclusions. You’ll learn the basics of statistical thinking – starting with an interesting question and some data.

Average: 6.5 (2 votes)
May 22nd 2017

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.

Average: 8.3 (6 votes)
May 22nd 2017

This course provides an analytical framework to help you evaluate key problems in a structured fashion and will equip you with tools to better manage the uncertainties that pervade and complicate business processes. The course aim to cover statistical ideas that apply to managers. We will consider two basic themes: first, is recognizing and describing variations present in everything around us, and then modeling and making decisions in the presence of these variations.

Average: 8.5 (2 votes)
Feb 27th 2017

This short course will provide an introductory, hands-on introduction to statistics used in educational research and evaluation. Participants will learn statistical concepts, principles, and procedures by building Excel spreadsheets from scratch in a guided learning approach using very short video-based tutorials.

Average: 7.5 (4 votes)
Nov 1st 2016

Learn data analysis basics for working with biomedical big data with practical hands-on examples using R. This course provides a broad foundation of statistical terms and concepts as well as an introduction to the R statistical software package. The topics covered are fundamental components of biostatistical methods used in both omics and population health research.

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