Statistical Inference

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. Furthermore, there are broad theories (frequentists, Bayesian, likelihood, design based, …) and numerous complexities (missing data, observed and unobserved confounding, biases) for performing inference. A practitioner can often be left in a debilitating maze of techniques, philosophies and nuance. 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 inference and use this information for making informed choices in analyzing data.

There are 4 modules in this course:

1. Probability and Expected Values
2. Variability, Distribution & Asymptotics
3. Intervals, Testing & Pvalues
4. Power, Bootstrapping & Permutation Tests

This course is available in 27 languages: English (Original), Svenska (auto), 한국어 (자동), O‘zbek (avtomatik), Ελληνικά (αυτόματο), Português (Brasil) (auto), Italiano (auto), Español (auto), العربية (آلي), Tiếng Việt (tự động), ไทย (อัตโนมัติ), 日本語 (オート), Azərbaycan dili (avto), Polski (automatyczny), دری (خودکار), Nederlands (auto), Türkçe (otomatik), Deutsch (Auto), हिन्दी (ऑटो), پښتو (خودکار), Русский (авто), Français (aut.), Magyar (automata), 中文（简体） (自动), Українська (авто), Bahasa Indonesia (otomatis), Қазақша (автоматтық)

*Take advantage of the 7-day free trail, apply for financial aid or pay the course fee.

*Access to this course requires the user to register or create an account on the course platform.