1. Sampling and sampling distibutions

2. Sampling from a finite and an infinite population Simple random sample (finite population) – Population size N, sample size n – Each possible sample of size n has the same probability of being selected Random sample (infinite population) – Each element comes from the same population Making sure all the cereal boxes have the same weight at the plant – Each element is selected independently Sampling customers of a McDonalds restaurant

3. The number of different possible samples N=2500, n = 30 N!/(n!*(N-n)!)=2.57*10^69

4. Point estimation Finding the sample mean Population mean = $51,800 Population standard deviation = $4000

5. Sampling distributions

6. An example, sample size 30, population standard deviation 4000

8. Central limit theorem

9. TETC-110B

10. Sampling distributions

11. The distribution function for sample proportion Can be approximated by a normal distribution – If np>=5 – and n(1-p)>=5