pl.sci 547 ~ spring 2011 - university of idaho...introduction to biometrics experimental design...
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Biometrics for Plant Scientists
Pl.Sci 547 ~ Spring 2011
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Biometrics for Plant Scientists
Plant Science 547
Spring 2011
Jack Brown
Office (208) 885-7078
Cell (208) 301-4021
Email: [email protected]
Monday, Wednesday & Friday
9:30 to 10:20
Ag. Sci. 141
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Course Objective
Explain the use of biometrical
techniques in research with particular
emphasis in designing, analyzing and
interpreting agricultural and biological
experiments.
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Course Objective
This course will emphasize the
application of statistical methods to
biological experiments and outline
some of the problems that may be
encountered when applying these
techniques to biological systems.
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Introduction to Biometrics
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Introduction to Biometrics
Need for biometrical experiments.Estimation.
Error.
Probability theory.Binomial Distribution.
Normal Distribution.
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Use of computers in
Biometricsdata collection, sorting, analysis,
interpretation, summarization.
Introduction to SAS
Introduction to Biometrics
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Introduction to BiometricsTest # 1
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Introduction to Biometrics
Experimental Design
Test # 1
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Experimental Design
Single factor experiments.CRB, RCB, latin square, laticesquare, (0,1) designs.
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Multiple factor experiments.
factorial, nested, split-plot, strip-plot.
Experimental Design
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Restraints on experimental designstreatment, facility, time, money
factors, factor levels, replication
Experimental Design
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Introduction to Biometrics
Experimental Design
Test # 1
Test # 2
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Introduction to Biometrics
Experimental Design
Analysis of quantitative data
Test # 1
Test # 2
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Analysis of quantitative data
t-tests.
Analyses of variance.Theory.
t, & F distributions.
Assumptions of ANOVA.
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Completing an ANOVA.CRD, RCB, Latin square, latice
square, (0,1).factorial, nested, split-plot, strip-
plot.
Analysis of quantitative data
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Fixed v Random effects.
What are they?
Why does it matter?
Analysis of quantitative data
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Expected Mean Squares.Fixed model.
Random model.
Mixed model.
Analysis of quantitative data
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Multiple comparisons.Multiple range tests.
Orthogonal contrasts.
Trend analysis.
Analysis of quantitative data
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Introduction to Biometrics
Experimental Design
Analysis of quantitative data
Test # 1
Test # 2
Test # 3
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Introduction to Biometrics
Experimental Design
Analysis of quantitative data
Test # 1
Test # 2
Test # 3
Between characters, G x E
& Qualitative analyses
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Relationship between characters
Regression.
Linear.
Non-linear.
Transformations.
Multiple.
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Correlation.Covariance analysis.
Multivariate transformation.
Principal component analysis.
Relationship between characters
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G x E Interactions
Analysis of Variance.
Over sites
Over sites and years
Fixed v Random effects
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Interpretation.Visual.
Joint regression.
Probability analysis.
Additive main effects and multiplicative interactions (AMMI).
G x E Interactions
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Analyses of Qualitative Data
Chi-Square
How?
When?
and When not!
Non-parametric analyses
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Introduction to Biometrics
Experimental Design
Analysis of quantitative data
Test # 1
Test # 2
Test # 3
Test # 4
Between characters, G x E
& Qualitative analyses
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Data Presentation
Seminar
Poster
Paper
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Introduction to Biometrics
Experimental Design
Analysis of quantitative data
Test # 1
Test # 2
Test # 3
Test # 4
Final Exam?
Between characters, G x E
& Qualitative analyses
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90-100% - A
75-89% - B
60-74% - C
50-59% - D
Less than 49% - E
Grading
Potential of 5% increase in
grade for class participation
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Lecture Notes
http://courses.cals.uidaho.edu/pses/plsc547
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Introduction to Biometrics