diploma in statistics introduction to regression lecture 6.11 introduction to regression lecture 6.1...
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Diploma in Statistics Introduction to Regression Lecture 6.13 Introduction to Regression Lecture 6.1 Review Laboratory 2 More on indicators –two-sample t-tests –one way ANOVA –two regressions More on logs General issues in regressionTRANSCRIPT
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Diploma in StatisticsIntroduction to Regression
Lecture 6.1 1
Introduction to RegressionLecture 6.1
• Review Laboratory 2
• More on indicators
• More on logs
• General issues in regression
![Page 2: Diploma in Statistics Introduction to Regression Lecture 6.11 Introduction to Regression Lecture 6.1 Review Laboratory 2 More on indicators More on logs](https://reader036.vdocument.in/reader036/viewer/2022081605/5a4d1acb7f8b9ab05996f76f/html5/thumbnails/2.jpg)
Diploma in StatisticsIntroduction to Regression
Lecture 6.1 2
Introduction to RegressionLecture 6.1
• Review Laboratory 2
– estimating time series components– do big mammals have big brains?
Minitab
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Diploma in StatisticsIntroduction to Regression
Lecture 6.1 3
Introduction to RegressionLecture 6.1
• Review Laboratory 2
• More on indicators
– two-sample t-tests– one way ANOVA– two regressions
• More on logs
• General issues in regression
![Page 4: Diploma in Statistics Introduction to Regression Lecture 6.11 Introduction to Regression Lecture 6.1 Review Laboratory 2 More on indicators More on logs](https://reader036.vdocument.in/reader036/viewer/2022081605/5a4d1acb7f8b9ab05996f76f/html5/thumbnails/4.jpg)
Diploma in StatisticsIntroduction to Regression
Lecture 6.1 4
More on Indicators;two regressions
1086420
8
7
6
5
4
3
2
1
Temperature
Gas
Scatterplot of Gas vs Temperature
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Diploma in StatisticsIntroduction to Regression
Lecture 6.1 5
More on Indicators;two regressions
Homework
Create two subsets of the Gas Consumption data corresponding to Before and After Insulation. Calculate separate regressions. Compare with the results using an indicator.
![Page 6: Diploma in Statistics Introduction to Regression Lecture 6.11 Introduction to Regression Lecture 6.1 Review Laboratory 2 More on indicators More on logs](https://reader036.vdocument.in/reader036/viewer/2022081605/5a4d1acb7f8b9ab05996f76f/html5/thumbnails/6.jpg)
Diploma in StatisticsIntroduction to Regression
Lecture 6.1 6
Introduction to RegressionLecture 6.1
• Review Laboratory 2
– estimating time series components– do big mammals have big brains?
• More on indicators
– two-sample t-tests– one way ANOVA– two regressions
• More on logs
![Page 7: Diploma in Statistics Introduction to Regression Lecture 6.11 Introduction to Regression Lecture 6.1 Review Laboratory 2 More on indicators More on logs](https://reader036.vdocument.in/reader036/viewer/2022081605/5a4d1acb7f8b9ab05996f76f/html5/thumbnails/7.jpg)
Diploma in StatisticsIntroduction to Regression
Lecture 6.1 7
More on logs• The log transformation
– Normalises skew distributions
– equalises unequal standard deviations
![Page 8: Diploma in Statistics Introduction to Regression Lecture 6.11 Introduction to Regression Lecture 6.1 Review Laboratory 2 More on indicators More on logs](https://reader036.vdocument.in/reader036/viewer/2022081605/5a4d1acb7f8b9ab05996f76f/html5/thumbnails/8.jpg)
Diploma in StatisticsIntroduction to Regression
Lecture 6.1 8
More on logs• The log transformation
– converts multiplicative models to additive
XY
XloglogYlog
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Diploma in StatisticsIntroduction to Regression
Lecture 6.1 9
Introduction to RegressionLecture 6.1
• Review Laboratory 2
• More on indicators
• More on logs
• General issues in regression
![Page 10: Diploma in Statistics Introduction to Regression Lecture 6.11 Introduction to Regression Lecture 6.1 Review Laboratory 2 More on indicators More on logs](https://reader036.vdocument.in/reader036/viewer/2022081605/5a4d1acb7f8b9ab05996f76f/html5/thumbnails/10.jpg)
Diploma in StatisticsIntroduction to Regression
Lecture 6.1 10
General Issues in Regression
• Degree of control of the study environment
• Stability of relationships
• Extrapolation
• Predicting explanatory variables
• Large data sets
– many cases
– many variables
![Page 11: Diploma in Statistics Introduction to Regression Lecture 6.11 Introduction to Regression Lecture 6.1 Review Laboratory 2 More on indicators More on logs](https://reader036.vdocument.in/reader036/viewer/2022081605/5a4d1acb7f8b9ab05996f76f/html5/thumbnails/11.jpg)
Diploma in StatisticsIntroduction to Regression
Lecture 6.1 11
General Issues in Regression
Beware of
• undiagnosed regression equations
• small samples
– representative?
– wide prediction interval
• changing systems
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Diploma in StatisticsIntroduction to Regression
Lecture 6.1 12
General Issues in Regression
Exploratory data analysis invariably
• raises unanticipated issues,
• helps clarify issues,
• though not necessarily resolving them
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Diploma in StatisticsIntroduction to Regression
Lecture 6.1 13
General Issues in Regression
"The justification sometimes advanced that a multiple regression analysis on observational data can be relied upon if there is
an adequate theoretical background
is utterly specious and
disregards the unlimited capability of the human intellect for producing plausible explanations by the carload lot".
K.A. Brownlee (1965) "Statistical Theory and Methodology", New York, Wiley.
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Diploma in StatisticsIntroduction to Regression
Lecture 6.1 14
Reading
SA § 1.6, §§8.7 - 8.8
Hamilton Ch. 3, pp. 84 - 95, Ch. 5, pp. 148 - 158