1. Models, parameters and GLMs
Quantitative Methods
Models, parameters and GLMs

2. Models Models, parameters and GLMs Y =  + 
Unknown quantities we would like to know, in Greek
Known quantities that are estimates of them, in Latin

3. Models, parameters and GLMs
General Linear Model

4. Models, parameters and GLMs
Aliassing

5. Models, parameters and GLMs
Aliassing

6. Models, parameters and GLMs
Aliassing

7. Models, parameters and GLMs
Aliassing

8. Models, parameters and GLMs
GLMs in Minitab √

9. Logic of statistical inference
Models, parameters and GLMs
Logic of statistical inference
God’s view: , 1, 2 are known, and y, a1, a2 are unpredictable
Our view: y, a1, a2 are known, and we need to guess , 1, 2

10. Logic of statistical inference
Models, parameters and GLMs
Logic of statistical inference
true 1
possible a1
observed a1
inferred 1

11. Logic of statistical inference
Models, parameters and GLMs
Logic of statistical inference
true 1
possible a1
observed a1
inferred 1

12. Logic of statistical inference
Models, parameters and GLMs
Logic of statistical inference
true 1
possible a1
observed a1
inferred 1

13. Logic of statistical inference
Models, parameters and GLMs
Logic of statistical inference
true 1
possible a1
observed a1
inferred 1

14. Logic of statistical inference
Models, parameters and GLMs
Logic of statistical inference
true 1
possible a1
observed a1
inferred 1

15. Simulations in Minitab
Models, parameters and GLMs
Simulations in Minitab

16. Simulations in Minitab
Models, parameters and GLMs
Simulations in Minitab

17. Simulations in Minitab
Models, parameters and GLMs
Simulations in Minitab

18. Simulations in Minitab
Models, parameters and GLMs
Simulations in Minitab

19. Simulations in Minitab
Models, parameters and GLMs
Simulations in Minitab √

20. Simulations in Minitab
Models, parameters and GLMs
Simulations in Minitab

21. Simulations in Minitab
Models, parameters and GLMs
Simulations in Minitab

22. Next week: Using more than one explanatory variable
Models, parameters and GLMs
Last words…
GLMs unite ANOVA (categorical X) and regression (continuous X), and use model formulae
‘Parameter’ and ‘estimate’ are central ideas
Enjoy playing God for once, and knowing all the answers
Next week: Using more than one explanatory variable
Read Chapter 4