Quiz 1 Study Guide

Quiz 1 Study Guide - Study Guide for Individual Group Quiz...

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Study Guide for Individual & Group Quiz 1 Stat 200 Sections 9-12 Mon Sept 17 during scheduled lab in 214 Boucke Chapter 1 Definition of statistics - A collection of procedures and principles for gathering data and analyzing information to help people make decisions when faced with uncertainty. Population versus sample - Population : all observations or measurements that are ideally of interest. - Sample: the observations or measurements that are obtained Be able to recognize the important statistical principles found on page 8 when given choices (don’t need to memorize) - Simple summaries of data tell a story and are easier to digest than long lists. - When discussing the change in rate or risk of occurrence, include the base rate or base risk. - A representative sample of only a few hundred or thousand can tell a story about millions. - An unrepresentative sample, no matter how large, tells you nothing. - Cause-and-effect conclusions cant be made using observational studies. - Cause-and effect conclusions can be made on the basis of randomized experiements. - A statistically significant finding doesn’t always have practical significance. You must find out the magnitude of the relationship or difference. “randomized” experiment versus observational study. - Observational study : A study in which participants are merely observed and measured. Comparisons based on observational studies are comparisons of naturally occurring groups. - Randomized experiment: A study in which treatments are randomly assigned to participants. Chapter 2: Section 2.1-2.3 What the term raw data (unsummarized) means. - Term used for numbers and category labels that have been collected but have not yet been processed in any way. Symbol for sample size - n How to distinguish between categorical and quantitative variables - Categorical variable : Consists of group or category names that don’t necessarily have any logical ordering. Each individual falls into one and only one category. Most fundamental summaries are how many individuals, and what percent of individuals fall into each category. Ex: country of residence, eye color. - Quantitative variable : Raw data are recorded as numerical values, and the data are either measurements or counts taken on each individual. Averaging. Ex: height, weight, hours of sleep last night, years of education, etc. The terms explanatory variable and response variable .
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