The Resource Linear methods for optimization and prediction in healthcare : make causal inferences in health data using R and Python, with Aileen Nielsen

Linear methods for optimization and prediction in healthcare : make causal inferences in health data using R and Python, with Aileen Nielsen

Label
Linear methods for optimization and prediction in healthcare : make causal inferences in health data using R and Python
Title
Linear methods for optimization and prediction in healthcare
Title remainder
make causal inferences in health data using R and Python
Statement of responsibility
with Aileen Nielsen
Creator
Subject
Language
eng
Summary
"Linear methods have traditionally been the workhorse of data analysis in many domains, and health-related applications are no exception. However, linear methods have a lot more to offer than standard regression analysis. This video explains why linear thinking remains a powerful and sophisticated way to think about data for prediction, causal analysis, and optimization in health tech. Designed for data scientists and for data savvy health care managers and clinicians, it demonstrates how to strengthen the conclusions you draw from health-related data and how to better allocate your health care resources."--Resource description page
Cataloging source
UMI
Characteristic
videorecording
http://library.link/vocab/creatorName
Nielsen, Aileen
LC call number
R859.7.D35
http://bibfra.me/vocab/relation/on-screenpresenter
EYMsr9-etL4
PerformerNote
Presenter, Aileen Nielsen
Runtime
94
http://library.link/vocab/subjectName
  • Medical care
  • Quantitative research
  • Linear models (Statistics)
  • Data mining
Technique
live action
Label
Linear methods for optimization and prediction in healthcare : make causal inferences in health data using R and Python, with Aileen Nielsen
Link
http://databases.mvlc.org/connect/safari?uiCode=&xmlId=9781491991213
Instantiates
Publication
Note
  • Title from title screen (Safari, viewed December 6, 2017)
  • Release information from resource description page (Safari, viewed December 6, 2017)
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Configuration of playback channels
unknown
Content category
two-dimensional moving image
Content type code
  • tdi
Content type MARC source
rdacontent
Control code
on1014123532
Dimensions
unknown
Extent
1online resource (1 volume)
Form of item
online
Media category
  • computer
  • video
Media MARC source
  • rdamedia
  • rdamedia
Media type code
  • c
  • v
Medium for sound
other
Other physical details
illustrations.
Sound
sound
Sound on medium or separate
sound on medium
Specific material designation
  • remote
  • other
Stock number
CL0500000919
System control number
(OCoLC)1014123532
Video recording format
other
Label
Linear methods for optimization and prediction in healthcare : make causal inferences in health data using R and Python, with Aileen Nielsen
Link
http://databases.mvlc.org/connect/safari?uiCode=&xmlId=9781491991213
Publication
Note
  • Title from title screen (Safari, viewed December 6, 2017)
  • Release information from resource description page (Safari, viewed December 6, 2017)
Carrier category
online resource
Carrier category code
  • cr
Carrier MARC source
rdacarrier
Color
multicolored
Configuration of playback channels
unknown
Content category
two-dimensional moving image
Content type code
  • tdi
Content type MARC source
rdacontent
Control code
on1014123532
Dimensions
unknown
Extent
1online resource (1 volume)
Form of item
online
Media category
  • computer
  • video
Media MARC source
  • rdamedia
  • rdamedia
Media type code
  • c
  • v
Medium for sound
other
Other physical details
illustrations.
Sound
sound
Sound on medium or separate
sound on medium
Specific material designation
  • remote
  • other
Stock number
CL0500000919
System control number
(OCoLC)1014123532
Video recording format
other

Library Locations

    • Merrimack Valley Library ConsortiumBorrow it
      4 High Street, Suite 175, North Andover, MA, 01845, US
      42.7009413 -71.1255084
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