Learning Statistics. Episode 22, Time Series Analysis
(2019, original release: 2017)

Nonfiction

eCourse

Provider: Kanopy

Details

PUBLISHED
The Great Courses, 2017
[San Francisco, California, USA] : Kanopy Streaming, 2019
DESCRIPTION

1 online resource (streaming video file) (34 minutes): digital, .flv file, sound

ISBN/ISSN
6733204
LANGUAGE
English
NOTES

Title from title frames

Time series analysis provides a way to model response data that is correlated with itself, from one point in time to the next, such as daily stock prices or weather history. After disentangling seasonal changes from longer-term patterns, consider methods that can model a dependency on time, collectively known as ARIMA (autoregressive integrated moving average) models

Film

In Process Record

Talithia Williams

Originally produced by The Great Courses in 2017

Mode of access: World Wide Web

In English

Additional Credits