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Unformatted text preview: Chapter 1: Introduction to Statistics and Data Analysis 1 CHAPTER 1 — INTRODUCTION TO STATISTICS AND DATA ANALYSIS Theme for the course: “The manner in which data are generated and collected determines the conclusions a statistician may draw from them.” Our semester will be spent building up a structured manner of thought and applying it to various types of applied problems. Keep this theme in mind as we continue throughout the semester, and ask about it if you think you’re losing the connection. We’ll encounter a lot of numerical exercises, but the structure and logic of the course is important to keep in mind… especially as you move beyond the semester. When most people hear the word “statistics,” they typically think of numbers, charts, and graphs… but these comprise only one part of the field! The study of statistics can be split into two categories: Descriptive Statistics Graphical and numerical methods for organizing and summarizing information. Inferential Statistics Methods for making conclusions about a population (and describing the reliability of these conclusions) using information obtained from a sample of the population. Terminology • Population the whole class of individuals about whom an investigator wants to generalize. • Sample the part of the population the investigator examines. • Inferences generalizations about the population that come from the sample. • Parameter numerical facts about the population. • Statistics estimates of the parameters computed from the sample. In the rest of this chapter, we discuss various settings in which conclusions are drawn from data, and we examine the role sampling and study design play in the results that are obtained. Chapter 1: Introduction to Statistics and Data Analysis 2 SCENARIO 1  SAMPLING Let’s consider a fictitious upcoming presidential race between L.E. Fant (the Republican candidate) and Don Key (the Democratic candidate). Suppose your supervisor at a media outlet directs you to conduct a poll to predict the outcome of the election. What is the population of interest? What is the parameter of interest? Why not talk to everyone (i.e., take a census )? This should give us the correct answer! Okay, maybe a sample is a good idea. What characteristics should my sample have? How might we ensure that the sample has these characteristics? Chapter 1: Introduction to Statistics and Data Analysis 3 Possible methods: Simple Random Sampling – Imagine putting all potential voters’ names on slips of paper in a box, mixing the slips really well, and drawing out a fixed number (say 1500). – Random chance determines the composition of our sample. – Every possible set of 1500 voters has the same chance of being selected....
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 Spring '08
 Noe
 Statistics, Simple random sample, observational studies

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