A Practical Guide to Basic StatisticsChapter 1 Part I: An Outline of the Basic TerminologyAs with any field of study, in order to begin to be able to understand and work with statistics, it is crucial to start out with a basic vocabulary--the terminology that is commonly used. In this chapter, I will provide a basic overview of important terminology in statistics, and then we will add further concepts andterms to this list, as you learn about them in the chapters to come. I feel that this material will be most useful to you if I set it up in a glossary format, so that the terms are easy to find for future reference. The most important place to begin would seem to be with the name of the field itself--‘statistics’--a word that can be used in more than one way, and therefore is often initially confusing to students.Statistics: a set of procedures for organizing and analyzing information (‘data’)However, this term is also sometimes used to refer to the resultsof some calculation on data (as in sports statistics, or census statistics: “the average American Family has 2.4 children”). While it may seem impossibly confusing at first to have the same term used both for the process of analyzing and the results of the analysis, oddly enough, in practice it is not particularly difficult to keep the usage straight. For example, Stacy might say “I am studying statistics this quarter,” in which case you would assume thatshe meant that she was learning the processes for organizing and analyzing data--it is unlikely, after all, that she would spend her quarter memorizing specific research test results. On the other hand, if Stacy said, “I have a copy of the statistics for this baseball team,” you would assume that she meant that she hadcalculated values on the baseball team, which were the results of the team’s performance being analyzed.The term ‘data’ is sometimes used informally as a synonym for ‘information’, but in the field of statistics, it has a more precise meaning:Data:(pl.,) information that has been put into numerical form (for the purposes of analysis)examples: weight, running speed, test score, amount of calories consumed, etc… Population: the complete set of “events” (or information) in which we are interested. “Events” can be test scores, voter opinions, dessert preferences, etc.Sample:a subset of the population —the set of actual observations that you’ve been able to obtain.Ideally, in most cases, every researcher would love to be able collect population information, but it is often not possible, due to expense, availability, or privacy issues. Parameters: numerical (computed) values that summarize the populationdata.An example of a parameter would be the population mean, or average.