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Chapter 1

Chapter 1. Why Study Statistics?. Dealing with Uncertainty. Everyday decisions are based on incomplete information. Dealing with Uncertainty. versus. The price of IBM stock will be higher in six months than it is now. .

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Chapter 1

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  1. Chapter 1 Why Study Statistics?

  2. Dealing with Uncertainty Everyday decisions are based on incomplete information

  3. Dealing with Uncertainty versus The price of IBM stock will be higher in six months than it is now. The price of IBM stock is likely to be higher in six months than it is now.

  4. Dealing with Uncertainty versus If the federal budget deficit is as high as predicted, interest rates will remain high for the rest of the year. If the federal budget deficit is as high as predicted, it is probable that interest rates will remain high for the rest of the year.

  5. Sampling Population and Sample A population is the complete set of all items in which an investigator is interested. A population is the set of all of the outcomes from a system or process that is to be studied. N represents population size.

  6. Examples of Populations • Names of all registered voters in Coles County, Illinois. • Incomes of all families living in the Charleston-Mattoon Area. • Annual returns of all stocks traded on the New York Stock Exchange. • Grade point averages of all the students at Eastern Illinois University.

  7. Sampling Population and Sample A sample is an observed subset of population values with sample size given by n.

  8. Sampling Random Samples Simple random sampling is a procedure in which every possible sample of n objects is equally likely to be chosen.

  9. Sampling Random Samples Simple random sampling is a procedure in which every possible sample of n objects is equally likely to be chosen. The resulting sample is usually called a random sample.

  10. Making Decisions Data, Information, Knowledge • Data: specific observations of measured numbers. • Information: processed and summarized data yielding facts and ideas. • Knowledge: selected and organized information that provides understanding, recommendations, and the basis for decisions.

  11. Making Decisions Descriptive and Inferential Statistics Descriptive Statisticsinclude graphical and numerical procedures that summarize and process data and are used to transform data into information.

  12. Making Decisions Descriptive and Inferential Statistics Inferential Statistics provide the bases for predictions, forecasts, and estimates that are used to transform information to knowledge.

  13. The Journey to Making Decisions Decision  Knowledge Experience, Theory, Literature, Inferential Statistics, Computers Information Descriptive Statistics, Probability, Computers Begin Here: Identify the Problem Data

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