1. Why Statistics? meaningful questions - systematic methods

2. General Overview “In most mathematics courses, the problem is solved when you obtain the numerical answer. In statistics, the problem is just beginning.” “In most mathematics courses, the problem is solved when you obtain the numerical answer. In statistics, the problem is just beginning.” –Daren Starnes

3. General Overview “Statistics is about data. Data are numbers, but they are not just numbers. Data are numbers with a context.” “Statistics is about data. Data are numbers, but they are not just numbers. Data are numbers with a context.” –YMS, p. xii

4. General Overview “All models are wrong. Some models are useful.” “All models are wrong. Some models are useful.” –George E.P. Box “There are three kinds of lies: lies, damned lies, and statistics.” “There are three kinds of lies: lies, damned lies, and statistics.” –Benjamin Disraeli

5. General Overview “53.8% of all statistics are made up.” “53.8% of all statistics are made up.” –The back of a package of wipes from Hooters

6. General Overview “An anonymous sage once defined a statistician as “one who collects data and draws confusions.” “An anonymous sage once defined a statistician as “one who collects data and draws confusions.” –CCMC, p. 1

7. Statistics vs. Other Math Courses “The formation of a statistics question requires an understanding of the difference between a question that anticipates a deterministic answer and a question that anticipates an answer based on data that vary.” “The formation of a statistics question requires an understanding of the difference between a question that anticipates a deterministic answer and a question that anticipates an answer based on data that vary.” –ASA, 2005

8. Statistics vs. Other Math Courses Context Context Variability Variability Estimation Estimation Research Design Research Design Data Collection Data Collection Interpretation Interpretation Writing Writing

9. Statistics vs. Other Math Courses Context Context Variability Variability Estimation Estimation Research Design / Data Collection Research Design / Data Collection Writing Writing

10. Statistics vs. Other Math Courses How fast is this car going? How fast is this car going? –Leads to a single discreet answer – Mathematical Thinking How fast are cars going on I-85 between I-77 and Concord Mills? How fast are cars going on I-85 between I-77 and Concord Mills? – Involves Context, Variability, Estimation, Research Design, and Writing – Statistical Thinking

11. Why Statistics? Some understanding of statistics helps all educational leaders in the current policy climate. Some understanding of statistics helps all educational leaders in the current policy climate. –Program evaluation –Emphasis on test scores –NCLB –Becoming a reflective practitioner –Becoming a researcher / practitioner

12. How Does Statistics Work? The Population The Population – The group about which you wish to make conclusions or generalizations – Defined by specific characteristics For our example dataset this semester For our example dataset this semester – All public school elementary teachers in the U.S. during the 1999-2000 school year

13. How Does Statistics Work? The Sampling Frame The Sampling Frame – The best available list of the members of the population – Should be as close actual population as possible For our example dataset this semester For our example dataset this semester – The list of all public schools in the U.S. according to the Common Core of Data from the National Center for Education Statistics (NCES)

14. How Does Statistics Work? The Sample The Sample – The group of participants you obtain for your study – Should be representative of the population For our example dataset this semester For our example dataset this semester – The participants in the Schools and Staffing Survey, 1999-2000 cohort – Public school teacher questionnaire, full time only

15. How Does Statistics Work?

16. Parameters Parameters – Quantitative indexes that describe characteristics of the population – The population “true scores”, what we would get if we collected data from the entire population, the result of conducting a census Statistics Statistics – Quantitative indexes that describe characteristics of the sample – The sample values that become our best guesses, or estimates, of population “true scores”, called parameters

18. Statistical Reasoning This course is about learning to use statistical reasoning to help offer some types of evidence as parts of the answers to questions about educational policy: This course is about learning to use statistical reasoning to help offer some types of evidence as parts of the answers to questions about educational policy: –Test theories –Evaluate educational interventions / strategies –Answer meaningful educational questions

19. The Curriculum Descriptive Statistics / Exploratory Data Analysis Descriptive Statistics / Exploratory Data Analysis Correlation / Regression Correlation / Regression Probability Probability Inferential Statistics Inferential Statistics – Means – Proportions / Percentages

20. Getting Started USA Today polls example USA Today polls example USA Today polls example USA Today polls example Electoral Vote tracker site Electoral Vote tracker site Electoral Vote tracker site Electoral Vote tracker site Gallup Polls Gallup Polls Gallup Polls Gallup Polls The course website The course website The course website The course website

21. Course Overview There is more than one way to unravel a statistics problem. There is more than one way to unravel a statistics problem. Connections with most disciplines abound in statistics. Connections with most disciplines abound in statistics.

22. Course Overview Make your midterm, final, and class presentation count for you. Find a dataset that has utility and meaning for you. Make your midterm, final, and class presentation count for you. Find a dataset that has utility and meaning for you.