Introduction to Probability and Statistics Fourteenth Edition - PowerPoint PPT Presentation

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Introduction to Probability and Statistics Fourteenth Edition

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  1. Introduction to Probability and StatisticsFourteenth Edition Introduction Train Your Brain for Statistics

  2. What is Statistics? What does a statistician do? Player Games Minutes Points Rebounds FG% Bob 34 32.7 24 7.6 .552 Andy 36 31.5 21 8.4 .465 Larry 30 33.0 18 5.6 .493 Michael 31 35.1 29 6.1 .422

  3. Job of a Statistician • Collects numbers or data • Organizes or arranges the data • Analyzes the data • Infers general conclusions

  4. Uses of Statistics • a theoretical discipline in its own right • a tool for researchers in other fields • used to draw general conclusions in a large variety of applications

  5. POLITICS If the election for mayor of Los Angeles were held today, who would you be more likely to vote for? James Hahn 32% Magic Johnson 36% Someone else 11% No opinion yet 21% • Forecasting and predicting winners • Where to concentrate • What should a statistician DO? (Cannot survey on every voter)

  6. INDUSTRY • To market product • Average length of life of a light bulb? • What should statistician do? (cannot test all the bulbs)

  7. Solution • Collect a smaller set of measurements that will (hopefully) be representative of the whole set. • POPULATION:set of all measurements • SAMPLE:A subset of population

  8. Definitions Variableis a characteristic that changes or varies over time and/or for different individuals or objects under consideration Experimental Unitsare items or objects on which measurements are taken Measurement results when a variable is actually measured on an experimental unit Populationis the WHOLE set of all possible measurements Sampleis a subset of population

  9. Examples • Light bulbs • Variable=lifetime • Experimental unit = bulb • Typical measurements: 1503.1 hrs, 1010.5 hrs

  10. Examples • Opinion polls • Variable = opinion • Experimental unit = person • Typical Measurements = Magic Johnson, someone else

  11. Examples • Hair color • Variable = Hair color • Experimental unit = Person • Typical Measurements = Brown, black, blonde

  12. Descriptive Statistics • When we can enumerate whole population, We use • DESCRIPTIVE STATISTICS:Procedures used to summarize and describe the set of measurements.

  13. Inferential Statistics • When we cannot enumerate the whole population, we use • INFERENTIAL STATISTICS:Procedures used to draw conclusions or inferences about the population from information contained in the sample.

  14. Objective of Inferential Statistics • To make inferences about a population from information contained in a sample. • The statistician’s job is to find the best way to do this.

  15. But, our conclusions could be incorrect…consider this internet opinion poll… • Internet users only • Measure of reliability We’ll PAY CASHFor Your Opinions! (as much as $50,000) ClickHere and sign up FREE!

  16. The Steps in Inferential Statistics • Define the objective of the experiment and the population of interest • Determine the design of the experiment and the sampling plan to be used • Collect and analyzethe data • Make inferences about the population from information in the sample • Determine the goodness or reliabilityof the inference.

  17. Key Words Experimental Unit Population Sample Descriptive Statistics Inferential Statistics