1. Preliminary Chapter Statistics: The science of learning from data Chapters 1-4: Tools and strategies for organizing, describing, analyzing data Chapter 5: How to produce data Chapter 6-9: Probability: The study of chance behavior Chapter 10-15: Testing Claims/Computing estimates

2. Ask the following questions Individuals = People Variables = Age, Gender, Job, Salary… Every set of data comes with background information to help us understand the data! 1. What individuals do the data describe? How many individuals are there? 2. How many variables? Defs of these variables? What units? (lbs? kilos?) 3. Reasons the data was gathered? (For a sample or population)?

3. Data Production Where can we find good data?  Library  Internet  www.nces.ed.gov (Nat’nl Center for Education Statistics website)  www.fedstats.gov (good source for projects) www.fedstats.gov  Statistical offices of foreign countries (www.statcan.ca, www.inegi.gob.mx )www.statcan.cawww.inegi.gob.mx

4. Is this good data? Suppose you want to find out if your classmates prefer cheeseburgers from McDonald's or Burger King. You decide to ask 50 people under the age of 20 which fast-food they prefer. In order to save time and energy, you conduct your survey at the McDonald’s closest to campus. Is there a problem with this?

6. Good and bad survey results In 1976, Shere Hite published The Hite Report on Female Sexuality, Seven Stories Press, Ny, Ny 2004. The conclusions reported in her book were based on 3,000 returned surveys from 100,000 surveys distributed by women’s groups. The results were that women were highly critical of men. In what way might the author’s findings have been biased?

8. W-6, H W-6H: Who What Why How Where When by Whom? Who – is being studied What – are the variables Why – was the data gathered How – was the data produced Where – was the data gathered When – was the data produced By Whom – who directed it, can we trust it?

9. StateRegionPopSAT verbal SAT math % taking % No HS Teacher pay ($1000) CAPAC358944995195418.954.3 COMTN46015515532711.340.7 CTNE35045125148412.553.6

10. More Defs! Exploratory Data Analysis: Examining data in order to describe their main features. (What do u see?) 2 steps 1) Examine the variables 2) Graph them. Distribution of a Variable: what values the variable takes on and how often it takes these values. The pattern of a variable is its distribution.

11. Do you wear your seat belt? Region% Wearing belts 2003 % Wearing belts 1998 NE7466.4 MW7563.6 South8078.9 West8480.8

12. Compare

13. Dotplots Number of goals scored by the US women’s soccer team in 34 games played in the 2004 season are: 3 0 2 7 8 2 4 3 5 1 1 4 5 3 1 1 3 3 3 2 1 2 2 2 4 3 5 6 1 5 5 1 1 5 What does this tell us about the performance of the US women’s team in 2004?

14. TI-83: 1 Var Stats L1

15. Exploring Relationships between variables Air travelers would like their flights to arrive on time. Airlines collect data about on-time arrivals and report them to the department of Transportation. Here’s one month’s data for flights from several western cities for two airlines: On timeDelayed Alaska Air3274501 American West6438787