Learning Statistics. Episode 14, Regression Predictions, Confidence Intervals.
(Streaming Film)
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Published
[San Francisco, California, USA] : The Great Courses, 2017., Kanopy Streaming, 2019.
Format
Streaming Film
Language
English
Notes
General Note
Title from title frames.
General Note
Film
General Note
In Process Record.
Participants/Performers
Talithia Williams
Date/Time and Place of Event
Originally produced by The Great Courses in 2017.
Description
What do you do if your data doesn't follow linear model assumptions? Learn how to transform the data to eliminate increasing or decreasing variance (called heteroscedasticity), thereby satisfying the assumptions of normality, independence, and linearity. One of your test cases uses the R data set for miles per gallon versus weight in 1973-74 model automobiles.
System Details
Mode of access: World Wide Web.
Citations
APA Citation, 7th Edition (style guide)
Williams, T. (2017). Learning Statistics . The Great Courses.
Chicago / Turabian - Author Date Citation, 17th Edition (style guide)Williams, Talithia. 2017. Learning Statistics. The Great Courses.
Chicago / Turabian - Humanities (Notes and Bibliography) Citation, 17th Edition (style guide)Williams, Talithia. Learning Statistics The Great Courses, 2017.
MLA Citation, 9th Edition (style guide)Williams, Talithia. Learning Statistics The Great Courses, 2017.
Note! Citations contain only title, author, edition, publisher, and year published. Citations should be used as a guideline and should be double checked for accuracy. Citation formats are based on standards as of August 2021.
MARC Record
Grouped Work ID
b737b0fe-a726-53a6-d91f-ed311f7e364d-eng
Grouping Information
Grouped Work ID | b737b0fe-a726-53a6-d91f-ed311f7e364d-eng |
---|---|
Full title | learning statistics episode 14 regression predictions confidence intervals |
Author | the great courses |
Grouping Category | movie |
Last Update | 2024-04-30 15:17:32PM |
Last Indexed | 2024-11-02 02:39:49AM |
Book Cover Information
Image Source | sideload |
---|---|
First Loaded | Sep 3, 2024 |
Last Used | Sep 22, 2024 |
Marc Record
First Detected | Aug 17, 2023 05:31:51 PM |
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Last File Modification Time | Apr 30, 2024 03:20:54 PM |
MARC Record
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