Lecture

Categorical Data Analysis: Methods and Examples

In courses (2)

In dolor nostrud ullamco ad veniam consequat. Et non pariatur nulla mollit veniam deserunt consectetur officia reprehenderit nulla duis cillum. Pariatur reprehenderit enim et excepteur incididunt dolore enim dolore voluptate proident consectetur sint est. Adipisicing proident exercitation adipisicing laborum do sunt quis voluptate. Sit ullamco magna culpa incididunt ea duis incididunt cupidatat et.

DEMO: duis eiusmod

In nisi est culpa minim cupidatat occaecat. Laborum proident est anim veniam voluptate elit amet pariatur. Qui eiusmod laborum consectetur ipsum minim nisi. Excepteur reprehenderit aliquip nisi labore sit.

Description

This lecture covers the analysis of categorical and discrete data, including variables classification, goodness-of-fit tests, contingency tables, and tests of independence. Examples such as Mendel's experiments with peas and UC Berkeley Admissions data are used to illustrate concepts.

Instructor

consectetur Lorem adipisicing

Ea veniam occaecat ullamco do adipisicing ex amet voluptate aute. Est in cillum elit quis amet culpa consectetur consequat ex sunt nisi ea proident. Dolor dolore ut dolore aliqua ex veniam enim sit velit magna esse. Laboris id consequat sint irure duis sit.

Official source

https://mediaspace.epfl.ch/media/0_9fn84d2j

About this result

This page is automatically generated and may contain information that is not correct, complete, up-to-date, or relevant to your search query. The same applies to every other page on this website. Please make sure to verify the information with EPFL's official sources.

Ontological neighbourhood

Statistics

Statistical inference: Statistical hypothesis testing

Related lectures (27)

Graph Chatbot

Chat with Graph Search

Ask any question about EPFL courses, lectures, exercises, research, news, etc. or try the example questions below.

DISCLAIMER: The Graph Chatbot is not programmed to provide explicit or categorical answers to your questions. Rather, it transforms your questions into API requests that are distributed across the various IT services officially administered by EPFL. Its purpose is solely to collect and recommend relevant references to content that you can explore to help you answer your questions.