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Economic Reasoning Using Statistics

Economic Reasoning Using Statistics. Econ 138 Dr. Adrienne Ohler. How you will learn. . Textbook: Intro Stats 4th Ed ., by Richard D. DeVeaux , Paul E. Velleman , and David E. Bock Digital copy available online with homeworks at http ://www.pearsonmylabandmastering.com/.

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Economic Reasoning Using Statistics

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  1. Economic Reasoning Using Statistics Econ 138 Dr. Adrienne Ohler

  2. How you will learn. • Textbook: Intro Stats 4th Ed., by Richard D. DeVeaux, Paul E. Velleman, and David E. Bock • Digital copy available online with homeworks at http://www.pearsonmylabandmastering.com/

  3. How To Register • Go to www.pearsonmylabandmastering.com • Follow notes on the last page of syllabus

  4. Class Websites • Homeworks: • http://www.pearsonmylabandmastering.com/ • Lectures & Handouts: • http://economics.illinoisstate.edu/aohler/eco138/index.shtml

  5. The rest of this class • Attendance Policy • Cellphone Policy • Assessment: • Homeworks(10 out of 12) • Due Sundays by 10:00pm • Quizzes (5 out of 6) • Exams • October 9th • November 20th • Cumulative Optional Final • Data Project

  6. Help for this Class • READ THE BOOK • Come to class prepared and awake • READ THE BOOK • Do your homework, repeatedly • READ THE BOOK • Office Hours: T, H 10-12am and by Appointment • READ THE BOOK • Get a tutor at the Visor Center

  7. Statistics • Statistics (the discipline) is a way of reasoning, a collection of tools and methods, designed to help us understand the world. • Statistics helps us to understand the real, imperfect world in which we live and it helps us to get closer to the unveiled truth.

  8. The language of Statistics • For literacy • 4 cows in a field • 7 cows by the road • 4 cows in a field on the left • 3 cows in a field on the right • Three options for parties: • Party A: Average age is 17 • Party B: Average age is 22 • Party C: Average age is 75

  9. What is Statistics Really About? • A statistic is a number that represents a characteristic of a population. (i.e. average, standard deviation, maximum, minimum, range) • Statistics is about variation.

  10. What Are Data? • Information • Data can be numbers, record names, or other labels. • Not all data represented by numbers are numerical data (e.g., 1=male, 2=female). • Data are useless without their context…

  11. Data Project • Objective: Ask a question and try to answer it using statistics. • Step 1: DATA COLLECTION - Due Wednesday September 4th in class. • Step 2: DESCRIPTION OF DATA – Due Monday September 16th in class • Step 3: QUESTIONS – Due Monday October 28th in class • Step 4: FINAL DATA PROJECT – Due by Thursday December 5th 5PM

  12. The “W’s” • To provide context we need the W’s • Who • What (and in what units) • When • Where • Why (if possible) • and How of the data. • Note: the answers to “who” and “what” are essential.

  13. Who • The Who of the data tells us the individual cases about which (or whom) we have collected data. • Individuals who answer a survey are called respondents. • People on whom we experiment are called subjectsor participants. • Animals, plants, and inanimate subjects are called experimental units. • Sometimes people just refer to data values as observations and are not clear about the Who. • But we need to know the Who of the data so we can learn what the data say.

  14. What and Why • Variables are characteristics recorded about each individual. • A categorical (or qualitative) variable names categories and answers questions about how cases fall into those categories. • Categorical examples: sex, race, ethnicity • A quantitative variable is a measured variable (with units) that answers questions about the quantity of what is being measured. • Quantitative examples: income ($), height (inches), weight (pounds)

  15. What and Why (cont.) • Ordinal variables measure the magnitude of a characteristic but without natural units. • Example: In a fitness evaluation, one question asked to evaluate the statement “I consider myself physically fit” on the following scale: • 1 = Disagree Strongly; • 2 = Disagree; • 3 = Neutral; • 4 = Agree; • 5 = Agree Strongly. • With an ordinal variable, look at the Why of the study to decide whether to treat it as categorical or quantitative.

  16. Counts Count • When we count the cases in each category of a categorical variable, the counts are not the data, but something we summarize about the data. • The category labels are the What, and • the individuals counted are the Who.

  17. Economic reasoning using statistics • What is economics? • The study of scarcity, incentives, and choices. • The branch of knowledge concerned with the production, consumption, and transfer of wealth. (google) • Wealth • The health, happiness, and fortunes of a person or group. (google) • What is/are statistics? • Statistics (the discipline) is a way of reasoning, a collection of tools and methods, designed to help us understand the world. • Statistics (plural) are particular calculations made from data. • Data are values with a context.

  18. Next Time… • Chapter 2 – Describing Categorical Variables • Data Project • Step 1: DATA COLLECTION - Due Thursday January 31st in class. • Ask yourself the who and what questions when collecting data.

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