Lecture_24,_Chap_11,_Sec_1

Lecture_24,_Chap_11,_Sec_1 - Chapter 11 Inferences On Two...

Info iconThis preview shows pages 1–10. Sign up to view the full content.

View Full Document Right Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon

Info iconThis preview has intentionally blurred sections. Sign up to view the full version.

View Full DocumentRight Arrow Icon
This is the end of the preview. Sign up to access the rest of the document.

Unformatted text preview: Chapter 11 Inferences On Two Samples Overview We continue with confidence intervals and hypothesis testing for more advanced models Models comparing two means When the two means are dependent When the two means are independent Models comparing two proportions Chapter 11 Section 1 Inference about Two Means: Dependent Samples Chapter 11 Section 1 Learning objectives Distinguish between independent and dependent sampling Test claims made regarding matched-pairs data Construct and interpret confidence intervals about the population mean difference of matched-pairs data 1 2 3 Two Means Dependent Samples Chapter 10 covered a variety of models dealing with one population The mean parameter for one population The proportion parameter for one population However, there are many real-world applications that need techniques to compare two populations Our Chapter 10 techniques do not do these Two Means Dependent Samples Examples of situations with two populations We want to test whether a certain treatment helps or not the measurements are the before measurement and the after measurement We want to test the effectiveness of Drug A versus Drug B We give Drug A to 40 patients We give Drug B to 40 patients The measurements are the Drug A and Drug B responses Two Means Dependent Samples In certain cases, the two samples are very closely tied to each other A dependent sample is one when each individual in the first sample is directly matched to one individual in the second In certain cases, the two samples are very closely tied to each other A dependent sample is one when each individual in the first sample is directly matched to one individual in the second Examples Before and after measurements (a specific persons before and the same persons after) Experiments on identical twins (twins matched with each other Helpful Hint: Read Example 1 on p. 575 of your textbook. Two Means Dependent Samples On the other extreme, the two samples can be completely independent of each other An independent sample is when individuals selected for one sample have no relationship to the individuals selected for the other On the other extreme, the two samples can be completely independent of each other An independent sample is when individuals selected for one sample have no relationship to the individuals selected for the other Examples Fifty samples from one factory compared to fifty samples from another Two hundred patients divided at random into two groups of one hundred Two Means Dependent Samples The dependent samples are often called matched-pairs Matched-pairs is an appropriate term because each observation in sample 1 is matched to...
View Full Document

This note was uploaded on 08/04/2008 for the course STAT 250 taught by Professor Sims during the Spring '08 term at George Mason.

Page1 / 29

Lecture_24,_Chap_11,_Sec_1 - Chapter 11 Inferences On Two...

This preview shows document pages 1 - 10. Sign up to view the full document.

View Full Document Right Arrow Icon
Ask a homework question - tutors are online