Workshop on Teaching Introductory Statistics Session 5: Finding and Using Real Data Roger Woodard, North Carolina State University Ginger Holmes Rowell, Middle Tennessee State University Medical College of Wisconsin in Milwaukee July 11, 2006

2 Overview  GAISE recommendations  Some specific sources for real data  Using data collection devises – an example & other sources of examples  Finding data for your topics

3 Pre-GAISE: Heeding the Call for Change (Cobb, 1992)  Students need to recognize that Personal decisions should be based on evidence (data) & acting on assumptions not supported by data can be dangerous Formulating problems & getting good data is difficult and time-consuming (experience makes a believer)

4 GAISE says: Use Real Data  Reasons for Use: Authenticity Considering collection or production issues Relating analysis to problem context Engaging students in thinking about relevant statistical concepts

5 GAISE: Understanding the Process  Students should understand the parts of the process through which statistics works … to obtain or generate data  “An important aspect of dealing with real data is helping students learn to formulate good questions and use data to answer them appropriately based on how the data were produced.” GAISE, Recommendation #2, paragraph 1

6 Understanding the Process: Various Examples  Have students formulate their hypotheses first (a separate hand-in homework)  Student generated surveys Question wordings – see how difficult (critique another groups survey questions) Question ordering (run an in class experiment)  Measurement Errors Students all take measurements and graphs the errors for the class

7 GAISE: Types of Data & Examples  Archival data surveys, websites, articles, Reader’s Digest  Class generated data surveys & quick polls, measurements, data about the students, experiments, data collection devises  Simulated data flip coins, roll dice, computer simulations

8 “Types” of Data, continued  GAISE Appendix descriptions Naked data (without context) Realistic data (could be a realistic scenario, but the data has been “made up”) Real data (the real thing)

9 Some Teaching Tips from GAISE  Make it interesting to STUDENTS(!)  Use a variety of contexts  Keep class generated contexts “safe”  Use data to answer questions relevant to the context  Show how data collected can generate new questions

10 Teaching Tips, continued  Use a “rich” data set for multiple topics Example: “Cicada Data” Real, timely, student collected, for biology students taking statistics Used for multiple topics  Descriptive statistics, graphical representations, writing reports  2-sample t-tests (gender)  ANOVA (3 species) DATA URL:

11 Specific Sources for Real Data  Using the Internet See handout  Examples - Archival Titanic dataset (compliments of Lisa Green) NBA dataset (compliments of Roger Woodard)

12 Specific Sources for Real Data  Examples – Student Generated Data Simple Examples  Beginning of the semester survey (short)  Estimate number of red books in the library  Examine variability around us – go outside and take some measurements (pine cones, leafs, …) Data Collection  Forensic cases (handouts)  Grip strength (demo)

13 Grip Strength Activity  Idea: Example of matched pairs Two measurements on one subject. One sample t-test.  Goal: Get students involved in the whole process: Collection through analysis. Carpenter example.

14 Grip Strength Activity  Makes use of TI-83/84 data collection probes. Many probes available including:  Heart rate, temperature, soil moisture, respiration, EKG, BP, light sensor, Accelerometers  Link to Calculators through CBL or through easy link.  Allow easy collection of data. 

15 Grip Strength Activity  Hand Dynamometer Measures grip strength in Newtons  Measure 10 volunteers Both right and left hand Record both values and take the difference

16 Grip Strength Activity  Students must make decisions about the data collection process. Issue of measurement error.  When do we measure? Sources of variability.  What position are students in when taking measures. Design issues.  Do we randomize?

17 Grip Strength Activity  Generate hypotheses Before data collected Think about hypotheses related to real situation.  Collect data Can use calculators to save time  Make conclusion About H 0 and about real situation

18 Specific Sources for Real Data  Examples – Simulated data We will generate simulated data in the technology sessions.

19 It’s Your Turn  Working in your groups, identify some datasets that

20 References  Cobb, George. (1992). Teaching statistics. In Lynn A. Steen (Ed.), Heeding the call for change: Suggestions for curricular action (MAA Notes No. 22),  GAISE College Report & Appendix, found at viewed 7/3/2006