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Intro to Statistics and Data

Intro to Statistics and Data. Chapter 1 Chapter 2. What is Statistics?. Statistics is the science of learning from data , and of measuring, controlling, and communicating uncertainty In a word: variation. Think , Show , Tell. Think first. Know where you are headed and why.

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Intro to Statistics and Data

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  1. Intro to Statistics and Data Chapter 1 Chapter 2

  2. What is Statistics? • Statistics is the science of learning from data, and of measuring, controlling, and communicatinguncertainty • In a word: variation

  3. Think, Show, Tell • Thinkfirst. Know where you are headed and why. • Show your work. The mechanics of the calculation are important but can not exist on their own. • Tellyour conclusion in the context of the problem

  4. What are these?

  5. Barry Bonds HRs by year

  6. Data • Information in context • Context: • Who • What (and in what units) • Why (if possible) • Where • When • How • By Whom

  7. The W’s • Who?-- The cases (or individuals) about which (or whom) we gather information • MLB Seasons from 1986 to 2007 • What? – Variables are characteristics recorded about each case • Barry Bonds’ HRs (HRs) • Why? – The reasons for gathering the data can influence our analysis, can help determine which type of variable

  8. The W’s cont. • When and where? – Help provide additional context for the data • How? – The methodology for gathering the data can determine whether you have useful information or pure crap

  9. More about What • Variables come in two types • A categorical (or qualitative) variable names categories and answers questions about how cases fall into those categories. (e.g., sex, race, ethnicity) • A quantitative variable is a measured variable (with units) that answers questions about the quantity of what is being measured. (e.g. income ($), height (inches), weight (pounds)) !!!Always include units!!!

  10. What can go wrong? • Don’t label a variable as categorical or quantitative without thinking about the question you want it to answer. • Just because your variable’s values are numbers, don’t assume that it’s quantitative. • Always be skeptical—don’t take data for granted.

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