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Intro to Statistics and Data

Discover the fundamental concepts of statistics, including variables, data gathering methodology, and the importance of context in analysis. Learn to differentiate between categorical and quantitative variables and always include units for accurate interpretation.

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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 there 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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