ECON1310 Lecture Notes - Lecture 6: Sampling Distribution, Binomial Distribution
Document Summary
P(x) = probability of x successes in n trials, with probability of success p on each trial. X = (cid:374)u(cid:373)(cid:271)er of (cid:858)su(cid:272)(cid:272)esses(cid:859) i(cid:374) sa(cid:373)ple, (cid:894)x = (cid:1004), (cid:1005), (cid:1006), , (cid:374)(cid:895) n = sample size (number of trials or observations) ncx = number of combinations p = pro(cid:271)a(cid:271)ility of (cid:858)su(cid:272)(cid:272)ess(cid:859) Sampling distribution of the sample proportion, when p=0. 5. If p 0. 5, the sa(cid:373)pli(cid:374)g distributio(cid:374) of the sa(cid:373)ple proportio(cid:374) will be skewed if the sa(cid:373)ple size is small. The sampling distribution of the sample proportion better approximates a normal distribution as n increases. The sampling distribution of the sample proportion can be approximated by a normal distribution if both: np > 5 and n(1-p)>5. Transforming the sampling distribution of the sample proportion to the z distribution. From the binomial distribution, if the sampling distribution of the sample proportion can be approximated as being normally distributed. Sampling distribution of the sample proportion to standardised normal distribution.
