Difference between revisions of "Least squares modelling (2014)"

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(Created page with "__NOTOC__{{ClassSidebar | date = 29 January 2013 to 13 February 2013 | dates_alt_text = | vimeoID1 = | vimeoID2 = | vimeoID3 = | vimeoID4 = | vimeoID5 = | vimeoID6 = | vimeoI...")
 
 
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__NOTOC__{{ClassSidebar
__NOTOC__{{ClassSidebarYouTube
| date = 29 January 2013 to 13 February 2013
| date = 29 January 2014 to 26 February 2014
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| dates_alt_text =  
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| course_notes_PDF = 2014-4C3-6C3-Least-squares-modelling.pdf  
| course_notes_PDF = 2014-4C3-6C3-Least-squares-modelling.pdf  
| course_notes_alt = Course slides
| course_notes_alt = Course slides
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| assignment_instructions =  
| assignment_instructions =  
| assignment_solutions =  
| assignment_solutions =  
| video_download_link_MP4 = http://learnche.mcmaster.ca/media/2014-4C3-6C3-Class-04B.mp4
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}}
}}
<span style="color:#900000">{{Huge|This page is out of date.}}</span> {{Huge|Please see the [[Least_squares_modelling |latest version of these notes]].}}


== Course notes and slides ==
== Course notes and slides ==
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* [http://learnche.mcmaster.ca/pid/?source=Least-squares Course textbook] (print chapter 4)
* [http://learnche.mcmaster.ca/pid/?source=Least-squares Course textbook] (print chapter 4)
* [[Image:Nuvola_mimetypes_pdf.png|20px|link=Media:2014-4C3-6C3-Least-squares-modelling.pdf ]] [[Media:2014-4C3-6C3-Least-squares-modelling.pdf |Slides for class]]  
* [[Image:Nuvola_mimetypes_pdf.png|20px|link=Media:2014-4C3-6C3-Least-squares-modelling.pdf ]] [[Media:2014-4C3-6C3-Least-squares-modelling.pdf |Slides for class]]  
{| class="wikitable"  style="text-align: center;"
|-
! Date
! Class number
! colspan="2"|Video and audio files
! Other materials
! Reading (PID)
! Slides
|-
| 29 January
| 04C
| [http://learnche.mcmaster.ca/media/2014-4C3-6C3-Class-04C.mp4 Video] (119 M) 
| [http://learnche.mcmaster.ca/media/2014-4C3-6C3-Class-04C.mp3 Audio] (18 M)
| None
| rowspan="10"|[http://learnche.mcmaster.ca/pid/?source=Least-squares Chapter 4]
| rowspan="10"|[[Image:Nuvola_mimetypes_pdf.png|20px|link=Media:2014-4C3-6C3-Least-squares-modelling.pdf]] [[Media:2014-4C3-6C3-Least-squares-modelling.pdf|Slides for class]]
|-
| 30 January
| 04D
| [http://learnche.mcmaster.ca/media/2014-4C3-6C3-Class-04D.mp4 Video] (304 M) 
| [http://learnche.mcmaster.ca/media/2014-4C3-6C3-Class-04D.mp3 Audio] (42 M)
| See the source code below
|-
| 03 February
| 05A
| [http://learnche.mcmaster.ca/media/2014-4C3-6C3-Class-05A.mp4 Video] (291 M) 
| [http://learnche.mcmaster.ca/media/2014-4C3-6C3-Class-05A.mp3 Audio] (41 M)
| See the source code below
|-
| 05 February
| 05B
| [http://learnche.mcmaster.ca/media/2014-4C3-6C3-Class-05B.mp4 Video] (216 M) 
| [http://learnche.mcmaster.ca/media/2014-4C3-6C3-Class-05B.mp3 Audio] (42 M)
| None
|-
| 06 February
| 05C
| [http://learnche.mcmaster.ca/media/2014-4C3-6C3-Class-05C.mp4 Video] (276 M)
| [http://learnche.mcmaster.ca/media/2014-4C3-6C3-Class-05C.mp3 Audio] (42 M)
| [[Media:2014-4C3-6C3-Least-squares-practice-problems.pdf|Practice problems]] (with partial solutions)
|-
| 10 February
| 06A
| [http://learnche.mcmaster.ca/media/2014-4C3-6C3-Class-06A.mp4 Video] (239 M)
| [http://learnche.mcmaster.ca/media/2014-4C3-6C3-Class-06A.mp3 Audio] (43 M)
| None
|-
| 12 February
| 06B
| [http://learnche.mcmaster.ca/media/2014-4C3-6C3-Class-06B.mp4 Video] (259 M)
| [http://learnche.mcmaster.ca/media/2014-4C3-6C3-Class-06B.mp3 Audio] (42 M)
| None
|-
| 13 February
| NA
| None
| None
| [[Written_midterm_-_2014|Collaborative midterm]]
|-
| 24 February
| 07A
| None
| None
| style="text-align: left;" |
* [[Media:Course-evaluation-2014.pdf|Course evaluation]]
* [[Media:Multiple-linear-regression-learning-2014.pdf|Multiple linear regression exercise]]
|-
| 26 February
| 07B
| [http://learnche.mcmaster.ca/media/2014-4C3-6C3-Class-07B.mp4 Video] (277 M)
| [http://learnche.mcmaster.ca/media/2014-4C3-6C3-Class-07B.mp3 Audio] (41 M)
| None
|}


== Software source code ==
== Software source code ==
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Take a look at [[Software_tutorial|the software tutorial]], particularly steps 16 to 22.
Take a look at [[Software_tutorial|the software tutorial]], particularly steps 16 to 22.


<!--
== Code used in class ==
== Code used in class ==


Least squares demo
Least squares demo; [http://www.r-fiddle.org/#/fiddle?id=kLmMLXev&version=1 run this code in your web-browser].
<syntaxhighlight lang="sas">
<syntaxhighlight lang="sas">
x <- c(10, 8, 13, 9, 11, 14, 6, 4, 12, 7, 5)
x <- c(10, 8, 13, 9, 11, 14, 6, 4, 12, 7, 5)
Line 62: Line 138:


coef(model.ls)
coef(model.ls)
confinf(model.ls)
confint(model.ls)


names(model.ls)
names(model.ls)
model$resisduals
model.ls$resisduals
resid(model.ls)
resid(model.ls)


Line 72: Line 148:
</syntaxhighlight>
</syntaxhighlight>


 
<!--
Thermocouple data
Thermocouple data
<syntaxhighlight lang="sas">
<syntaxhighlight lang="sas">

Latest revision as of 07:19, 4 January 2017

Class date(s): 29 January 2014 to 26 February 2014
Nuvola mimetypes pdf.png (PDF) Course slides

This page is out of date. Please see the latest version of these notes.


Course notes and slides

Date Class number Video and audio files Other materials Reading (PID) Slides
29 January 04C Video (119 M) Audio (18 M) None Chapter 4 Nuvola mimetypes pdf.png Slides for class
30 January 04D Video (304 M) Audio (42 M) See the source code below
03 February 05A Video (291 M) Audio (41 M) See the source code below
05 February 05B Video (216 M) Audio (42 M) None
06 February 05C Video (276 M) Audio (42 M) Practice problems (with partial solutions)
10 February 06A Video (239 M) Audio (43 M) None
12 February 06B Video (259 M) Audio (42 M) None
13 February NA None None Collaborative midterm
24 February 07A None None
26 February 07B Video (277 M) Audio (41 M) None

Software source code

Take a look at the software tutorial, particularly steps 16 to 22.

Code used in class

Least squares demo; run this code in your web-browser. 

x <- c(10, 8, 13, 9, 11, 14, 6, 4, 12, 7, 5)
y <- c(8.04, 6.95, 7.58, 8.81, 8.33, 9.96, 7.24, 4.26, 10.84, 4.82, 5.68)
plot(x,y)
model.ls <- lm(y ~ x)
summary(model.ls)

coef(model.ls)
confint(model.ls)

names(model.ls)
model.ls$resisduals
resid(model.ls)

plot(x, y)
abline(model.ls)


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