Experimental design Course development NSS Monday 7 Nov

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