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Experimental designCourse development
NSS
Monday 7 Nov
Experimental designCourse development
Intuitive approachesFitting equations to data (D&W)
Response surface approaches
Quantitative methods in …From model to design
ANOVA GLM approachesRandomization, blocking, replication
Balanced to unbalanced designsCRD, CRBD, LS, GLSCodingFrom design to model
Mixed model approachOptimal Design Criteria approach
Experimental designCourse development
• Practitioners
• Statistical staff
ANOVA GLM approaches
Different mathematical level
Different level of practice
Experimental designPractical exercises
Set of educationally perfect examples from different scientific disciplines
Starting with very simple example
OPDOE DROPBOX, WWW
Set up standard strategy for example description in R and MS-word
Data
Meta-dataTabular and graphical representations of design and dataResearch problem and hypothesis to testAnalysisPresentation of the results….
Experimental designPractical exercises
Form an R-team
Data base of examples on WWW
Start with what we have on OPDOE
Extend
Time table, team work, responsibilities
This week
Workshop Cuenca
Finalize before workshop of Jimma
We have 2 years!
This week’s planning
Discuss course outlines and strategies
Example problems
Standard description of examples in R
Structure of the educational platform
Monday 7 Nov
Week planningMo: strategy first brainstorming
Thu: examplesWed: standardized examplesTurs: integrateFri: wrap up
Discuss course outlines and strategies
Examples
Monday 7 Nov
Discuss course outlines and strategiesScience, engineering & technology
Biomedical sciencesHumanities & social sciences
Prerequisites, precalculus, calculus, baby stats, …
Computational platform. Engineering toolbox.
Statisticians practitioners
Approaches targeted to focus group
….
Examples of good exp
Monday 7 Nov: report group discussion
Sadi GarciaDep stats offers 2 courses for all fac
Baby stats. 5th sem. UNALM.Stats methods for research, inc DOE. 8th or 9th sem. Agronomy, An Sc
Ex desPrinciples. How to introduce replication, randomisation and blocking?Simple designs. CRD CRBD LS linked to ANOVA. MulComp.Factorial arrangementsRegression analysisANCOVA. Possible step from ANOVA to GLM
WeaknessPlanning. Factors? Levels?How select optimal DOE?
Practical, pragmatic, no computational exerciseR training prerequisite (in baby stats)Short course
Monday 7 Nov: report discussion
Ximena Reynafarje– First baby stats. Stats concepts and principles.– Stats methods for research
• Focused on maths
• No critical thinking
• Simple ex => understand implementation of theory
• Starting from research question => problem solving => design
• Basic principles should be understood, without prerequisites
– More emphasis on practical ex• Recognition of similarity between ex
– Optimal compromise between too practical and too theoretical• Range of ex of any application field
– What to do with repeated measures?• Autocorrelation?
• Add extra modules?
Monday 7 Nov: report discussion
Daniel Martinez– 3 courses Bac in Bucaramanga, Colombia
• Maths 2D
• Babybaby stats
• Exp Des
– Graphics => sampling strategy for two pop• Histogram => prob distr
• Hypothesis 2-means t-test
• Hypothesis 2-var t-test
• CRD
• CRBD
• Chisq indep test for contingency tables
• Excercises in XLS. Stats add-on.
• Intuitive approach. One-factor-at-a-time.
• Objective: do analysis independly.
– Epidemiology, only course that builds further on stats concept