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Statistics!

Statistics!. Today. Check in How is that proposal coming along…? Finish up material from Tuesday Statistics. Statistics. Purpose for today and Tuesday Familiarize you with statistical terms and concepts Help you get a general sense of statistics What are they? Why do we use them?

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Statistics!

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  1. Statistics!

  2. Today • Check in • How is that proposal coming along…? • Finish up material from Tuesday • Statistics

  3. Statistics • Purpose for today and Tuesday • Familiarize you with statistical terms and concepts • Help you get a general sense of statistics • What are they? • Why do we use them? • What are some basic statistics?

  4. What are they • Statistics are numbers that describe a sample • Parameters are numbers that describe a population

  5. What are statistics for? • We use them to describe our variables • Descriptive statistics • We use them to make inferences from samples to populations • Inferential statistics • This is why sampling and bias are so very important

  6. Basic descriptive statistics-frequencies • Frequencies • Remember: variables are divided into categories • Frequencies tell us how many are in each type of category • Frequencies can refer to the raw number, or the percent

  7. Frequency--example

  8. Types of variables • Nominal • Ordinal • Interval • Ratio

  9. Nominal • “named” variables • Can be represented with numbers but have no numerical qualities • There is no rank order • E.g. Red, blue, green cars • Male/female gender

  10. Nominal green blue red

  11. Ordinal • Variables that have “order” • We assign them a rank, and may use numbers • We don’t actually know how much the ranks differ • E.g. bad, worse, worst • Some of the time, most of the time, all of the time

  12. Ordinal 3 2 1

  13. Ordinal • We should not manipulate ordinal variables numerically • Add, subtract, multiply • Because we don’t know if the categories are exact • But in practice ordinal variables are numerically manipulated all the time

  14. Interval • Interval data is rank ordered • We know that the space from one to the next is “equal” • E.g. temperature • But interval data has “no true zero” • There can’t be a true absence of the thing being measured • Like temperature, zero is “arbitrary” • We decide what zero is

  15. Interval “heat” Less than 0 Even more less than 0 “0” 1 2 3 4

  16. Ratio Data • Like interval data • It is ordered • We know that the space from one rating to the next is “equal” • It has a “true zero” • There CAN be an absence of it • E.g. length, weight • You can have “zero” weight

  17. Ratio “Weight” 0 1 2 3 4

  18. Useful terms • Univariate—referring to a single variable • Bivariate—two variables • Multivariate—more than two variables • Proportion—a percent

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