• View the Talks
• 43 min
  1. How to design and evaluate a direct marketing test

  • Mr. Nigel Hathway
• 40 min
  2. How to build a model to improve response

  • Dr. Stuart Clarke
• 29 min
  3. How to evaluate results from direct marketing campaigns involving targeting

  • Mr. Tom Breur
• 61 min
  4. Advanced statistical techniques of direct marketing tests

  • Dr. Barry Leventhal
• 33 min
  5. Campaign optimisation

  • Mr. Paul Rowson

Printable Handouts

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Navigable Slide Index

1. Introduction
2. Agenda
3. Objectives of this talk
4. Terms and definitions
5. In statistics, what is an experiment?
6. Experimental unit
7. Response variables or dependent variables
8. Independent variables or factors
9. Experimental design
10. Order of experimentation
11. Model description
12. Research hypothesis
13. Analysis
14. Experiments with a single factor
15. Single factor experiments
16. Model description - basic assumptions
17. Fixed vs. random models
18. Random model
19. Analysis of variance (ANOVA) rationale (1)
20. Analysis of variance (ANOVA) rationale (2)
21. Single factor model
22. Data layout
23. Using sample estimates in model equation
24. ANOVA interprets and tests the treatment effect
25. Example: experiment on recruitment channels
26. Example ANOVA table
27. Single factor experiments - summary
28. Randomised blocks and Latin squares
29. Randomised bock and Latin square designs
30. Randomised block design
31. Latin squares (1)
32. Latin squares (2)
33. Latin square designs
34. Factorial experiments
35. What are factorial experiments
36. Factorial experiment example: traditional design
37. Comparisons enabled by the traditional design
38. Factorial experiment example: factorial design
39. Comparisons enabled by factorial design
40. Interactions
41. Two factor model
42. Generalisation of factorial experiments
43. Extensions to the factorial experiment
44. Analysis of experiments
45. Regression analysis
46. Regression models - single predictor variable
47. Multiple regression
48. Analysis of experiments - summary
49. Summary of main points
50. Suggested further reading

Topics Covered

• Objectives of the talk
• Terms and definitions used in statistical experiments
• Single factor experiments
• Model description
• Fixed vs random models
• Analysis of variance rationale (ANOVA)
• Example: experiment on recruitment channels
• Randomised blocks and latin squares
• Factorial experiments
• Analysis of experiments
• Example
• Summary of main points

Links

Series:

• Statistics of Direct Marketing

Categories:

• Marketing & Sales
• Technology & Operations

Talk Citation

Publication History

• Published on May 22, 2008