Statistical methods

Question 1

What do you need to know before you start your experiment?

Answer 1

• size of experiment
• type of experiment
• duration and sequencing of experiment
• species, strains/stocks
• adaptation
• group sizes, number of groups
• randomisation

Question 2

Large group will affect the standard deviation how?

Answer 2

Larger group –> smaller SD

Question 3

Why perform pilot experiments?

Answer 3

• Logistis - setup of experimental protocol
• effect size of treatment
• variation
• determine size of experiment (SD important)

Question 4

name shapes for dose-response curves

Answer 4

• linear response
• nonlinear, monotonic response (slope is either positive or negative all the way)
• nonlinear, nonmonotonic response (slope changes)
• binary response (threshold; none at all, suddenly everything)

Question 5

uni-variate statistics

Answer 5

• variables are
  
  • independent
  • large numbers studies
• Data tables are long and thin

can be analysed using ANOVA, t-test, linear regression, etc

Question 6

today it is not uni-variate statistics, but

Answer 6

• large number of variables
• few number of animals
• data tables are short and fat

This is done because

• cost efficient
• ethical
• follow rules and regulations
• other reasons

needs multivariate analysis, e.g. PCA

Question 7

What happens when you use classical statistics on “short and fat” data? I.e. why do we need multivariate data analysis?

Answer 7

• increased risk of false results (spurious results)
• information is lost regarding dependent variables (co-variation)