This preview shows pages 1–2. Sign up to view the full content.
This preview has intentionally blurred sections. Sign up to view the full version.
View Full Document
Unformatted text preview: 10.3 Comparing Two Population Means Defn: Two samples drawn from two populations are independent if the selection of one sample from one population does not affect the selection of the second sample from the second population. Otherwise, the samples are dependent . Notation: Two samples require appropriate subscripts. e.g. 1 and 2 , n 1 and n 2 Assumptions : 1. The two samples are independent. 2. The standard deviations 1 and 2 of the two populations are unknown but assumed to be equal, that is 1 = 2 . 3. At least one of the following is also true: i. Both samples are large (i.e. n 1 30 and n 2 30) ii. If either one or both sample sizes are small, then both populations from which the samples are drawn are normally distributed. Checking the Assumptions : The last assumption can be checked just like in Ch. 9. The first assumption can be checked by analyzing the experimental design. The second, however, can use math. rule of thumb about Assumption #2: okay if ratio of s max / s min < 2. Hypotheses : Although there are two population means (a.k.a. parameters) in our data structure, we consider them together as ONE parameter: 1 2 . Thus, we have H : 1 2 = 0 H A : 1 2 0 Note that we could use any value to compare to, but zero has a special interpretation....
View
Full
Document
This note was uploaded on 07/31/2011 for the course STAT 151 taught by Professor Henrykkolacz during the Winter '07 term at University of Alberta.
 Winter '07
 HenrykKolacz

Click to edit the document details