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
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
Course Objective
Explain the use of biometrical
techniques in research with particular
emphasis in designing, analyzing and
interpreting agricultural and biological
experiments.
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.
Introduction to Biometrics
Introduction to Biometrics
Need for biometrical experiments.Estimation.
Error.
Probability theory.Binomial Distribution.
Normal Distribution.
Use of computers in
Biometricsdata collection, sorting, analysis,
interpretation, summarization.
Introduction to SAS
Introduction to Biometrics
Introduction to BiometricsTest # 1
Introduction to Biometrics
Experimental Design
Test # 1
Experimental Design
Single factor experiments.CRB, RCB, latin square, laticesquare, (0,1) designs.
Multiple factor experiments.
factorial, nested, split-plot, strip-plot.
Experimental Design
Restraints on experimental designstreatment, facility, time, money
factors, factor levels, replication
Experimental Design
Introduction to Biometrics
Experimental Design
Test # 1
Test # 2
Introduction to Biometrics
Experimental Design
Analysis of quantitative data
Test # 1
Test # 2
Analysis of quantitative data
t-tests.
Analyses of variance.Theory.
t, & F distributions.
Assumptions of ANOVA.
Completing an ANOVA.CRD, RCB, Latin square, latice
square, (0,1).factorial, nested, split-plot, strip-
plot.
Analysis of quantitative data
Fixed v Random effects.
What are they?
Why does it matter?
Analysis of quantitative data
Expected Mean Squares.Fixed model.
Random model.
Mixed model.
Analysis of quantitative data
Multiple comparisons.Multiple range tests.
Orthogonal contrasts.
Trend analysis.
Analysis of quantitative data
Introduction to Biometrics
Experimental Design
Analysis of quantitative data
Test # 1
Test # 2
Test # 3
Introduction to Biometrics
Experimental Design
Analysis of quantitative data
Test # 1
Test # 2
Test # 3
Between characters, G x E
& Qualitative analyses
Relationship between characters
Regression.
Linear.
Non-linear.
Transformations.
Multiple.
Correlation.Covariance analysis.
Multivariate transformation.
Principal component analysis.
Relationship between characters
G x E Interactions
Analysis of Variance.
Over sites
Over sites and years
Fixed v Random effects
Interpretation.Visual.
Joint regression.
Probability analysis.
Additive main effects and multiplicative interactions (AMMI).
G x E Interactions
Analyses of Qualitative Data
Chi-Square
How?
When?
and When not!
Non-parametric analyses
Introduction to Biometrics
Experimental Design
Analysis of quantitative data
Test # 1
Test # 2
Test # 3
Test # 4
Between characters, G x E
& Qualitative analyses
Data Presentation
Seminar
Poster
Paper
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
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
Lecture Notes
http://courses.cals.uidaho.edu/pses/plsc547
Introduction to Biometrics