Foundations of Data Science: Inferential Thinking by Resampling

Online Course

edX
Foundations of Data Science: Inferential Thinking by Resampling

What is the course about?

Foundations of Data Science: Inferential Thinking by Resampling
The course Foundations of Data Science: Inferential Thinking by Resampling is an online class provided by University of California, Berkeley through edX. The skill level of the course is Introductory. It may be possible to receive a verified certification or use the course to prepare for a degree.
Learn how to use inferential thinking to make conclusions about unknowns based on data in random samples.
Course description
This course will teach you the power of statistical inference: given a random sample, how do we predict some quantity that we cannot observe directly? Using real-world examples from a wide array of domains including law, medicine and football, you’ll learn how data scientists make conclusions about unknowns based on the data available. Often, the data we have is not complete, yet we’d still like to draw inferences about the world and quantify the uncertainty in our conclusions. This is called statistical inference. In this course, you will learn the framework for statistical inference and apply them to real-world data sets.Notably, you will develop the practice of hypothesis testing—comparing theoretical predictions to actual data, and choosing whether to accept those predictions. This method allows us to evaluate theories or hypotheses about how the world works.You will also learn how to quantify the uncertainty in the conclusions you draw from hypothesis testing. This helps assess whether patterns that appear to be present in the data actually represent a true relationship in the world, or whether they might merely reflect random fluctuations due to noise. Throughout this course, we will go over multiple methods for estimation and hypothesis testing, based on simulations and the bootstrap method. Finally, you will learn about randomized controlled experiments and how to draw conclusions about causality.The course emphasizes the conceptual basis of inference, the logic of the decision-making process, and the sound interpretation of results.

Prerequisites & Facts

Foundations of Data Science: Inferential Thinking by Resampling

Course Topic

Computer Science, Data Analysis and Statistics

University, College, Institution

University of California, Berkeley

Course Skill Level

Introductory

Course Language

English

Place of class

Online, self-paced (see curriculum for more information)

Degree

Certificate

Degree & Cost

Foundations of Data Science: Inferential Thinking by Resampling

To obtain a verified certificate from edX / University of California, Berkeley you have to finish this course or the latest version of it, if there is a new edition. The class may be free of charge, but there could be some cost to receive a verified certificate (99.00 USD) or to access the learning materials. The specifics of the course may have been changed, please consult the provider to get the latest quotes and news.
University of California, Berkeley
Foundations of Data Science: Inferential Thinking by Resampling
provided by edX

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School: University of California, Berkeley
Topic: Computer Science, Data Analysis and Statistics
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