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Sept 17 - Measurement and Intro to Stats Last part.doc

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Physical Education and Sport
John Dunn

Sept 17 – Measurement and Testing continued • If we had only measured absenteeism, that would be a univariate test • If we had measured more than one variable, that would be a multivariate test Intro To Stats Why are stats useful? • Statistics condense large amounts of information into a few simple figures or statements • If we use stats, one number can summarize thousands of data points and tell us if an intervention is working well • Graphs are easy and quick to interpret, especially when we have lots of information to interpret Defining Stats • “A set of mathematical procedures for organizing, summarizing, and interpreting information.” • In the world of stats, we should all know what a number means and the laws of stats Where Do Our Data Come From? • Who/What are we interested in studying? • Data comes from objects (ex. Biomechanics studies golf balls, skis, clubs) • Population: All individuals (or objects) of interest in a particular study • Problem: very often, we cannot test (ex. Examine) the whole population (the PEDS 309 class is John Dunn’s population) • When we cant study an entire population, we study samples • Sample: “a set of individuals selected from a population, usually intended to represent the population in a research study” • Sample should represent the population • We are going to make inferences about populations based on sample data • We are going to get a sample and try to explain to the world what is happening • Problem: No guarantee that the sample scores will actually reflect the true score value for the population Sampling Error • Sampling error is the discrepancy, or amount of error, that exists between a sample statistic and the corresponding population parameter • Parameter – is used for population. A value that is usually numerical and describes a population • Statisti
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