This preview shows pages 1–3. 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: I NTRODUCTION TO S TATISTICS (S TAT200) W EEK #6 C ONFERENCE Sampling Distribution of the Same Means L ET ' S R EVIEW & S IMPL I FY . The GOAL of THIS Statistics class is to ENABLE you to get a handle on the statistical characteristics of a POPULATION based on SAMPLES of that population. You have certainly heard enough "polls" about projected Election results. These PREDICTED outcomes are based on SAMPLES of different populations of voters (e.g., females, Hispanics, males over age 50. etc.). They get some right and some wrong. We are expected to assume that these samples were representative of the specific group and randomly collected. D O YOU UNDERSTAND WHY WE MUST RELY ON SAMPLES OF A POPULATION RATHER THAN COLLECTING DATA ON THE ENTIRE POPULATION ? When could anyone EVER sample an entire population (Answer: The U.S. Census, but does this even include everyone?) W HAT ARE SOME QUESTIONS ABOUT THOSE SAMPLES? (Remember that we are dealing with only ONE variable at a time in this course, e.g., years of education OR annual income. We are NOT doing cause and effect like years of education AND annual income.) How do we collect a truly random sample? How do we collect a truly representative sample? What the difference between random and representative? How large do our samples have to be? How many samples of that size do we need to take? How do we analyze all these sample results and what do those results tell us about the entire population? The next step (next Chapter) will get into how CONFIDENT we can be that our sample results truly reflect the population's characteristic (one variable, remember). That issue is what the rest of the course is about. In this Week's Discussion, let's look at the impact (effect) of SAMPLE SIZE on the results we obtain compared to the TRUE POPULATION. Here are the ages of all 43 students in a f2f college class on Statistics. We will assume that this is an entire POPULATION. (This means we are NOT using this class as a sample of all UMUC Statistics classes. It is ONLY this class that we are interested in analyzing.). The ages: 21, 22, 26, 26, 27, 28, 29, 29, 30, 30, 31, 31, 31, 31, 32, 32, 34, 34, 34, 34, 34, 35, 35, 35, 36, 36, 36, 37, 37, 37, 37, 38, 40, 41, 41, 41, 42, 44, 44, 45, 48, 49, 49 What is the mean of this distribution of ages for this POPULATION?...
View
Full
Document
This note was uploaded on 10/03/2010 for the course STAT 200 taught by Professor Hirschorn during the Fall '10 term at University of Maryland Eastern Shore.
 Fall '10
 Hirschorn
 Statistics

Click to edit the document details