This document discusses sampling methods and how to select an appropriate sampling approach. It begins by defining a "perfect world" where everyone has an equal chance of being selected in a sample. It then discusses different target populations like mass markets versus niches. It provides examples of sampling methods like random digit dialing that can be more cost effective but less representative versus sampling from a fan list that is highly representative but more expensive. The document emphasizes considering the target population, survey goals, and potential biases to select the best sampling method and get accurate results. It stresses that biased samples can produce misleading or incorrect results.

1. First Find Your target By George Head

4. Perfect World Everyone in the universe of your project has an equal chance of getting selected Therefore the probability is 1 in N

5. Mass Markets 18 to 75 Living in Germany

7. Cost Efficiency Being Representative RDD High Low Expensive Cheap

9. Dealing with a Niche Bayern Munich

11. Cost Efficiency Being Representative RDD

13. Cost Efficiency Being Representative Sampling

15. Cost Efficiency Being Representative Fans List

18. Cost Efficiency Being Representative Sampling Ticket prices?

20. Cost Efficiency Being Representative Fans List Strip design?

22. Real life examples Brazilians in Rural England Home Projectors Large Lawns iPhone

23. Good sampling Method Identify the problem Who are you looking for? What the method? Objects of the survey. The BIAS. Refine the sampling Approach. Cost Efficient

24. Good sampling Method Identify the problem Who are you looking for? What the method? Objects of the survey. The BIAS. Refine the sampling Approach. Cost Efficient iPhone Home Projectors