1. Teaching Statistics Methods for Biology 1

2. Outline About stat 503 Students Course set up – Lecture – Project Challenges Teaching approach – Project design Self-defined project Instructor-defined project More relevant project, collaboration with labs? – Method selection system – Class discussion tool Clicker, Mixable and Hotseat 2

3. Stat 503— Statistical Methods for Biology Semester: Fall, spring, summer. Prerequisites/Corequisite: Mathematical experience at the level of one semester of calculus is required. Primary Audience: Biology, pharmacy, some agriculture and health science. Description: – Extensive coverage of statistical methods for mature students. – All examples and applications are drawn from the life, health and agricultural sciences. – Mathematical experience at the level of one semester of calculus is required, though no calculus is used in the course. 3

4. Student statistics(Fall, 2011) 4

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6. Lecture topic(Fall, 2011) Basic summary statistics and graphs Probability theory Binomial distribution Normal distribution Central limit theorem Sampling distribution Experiment and sampling design Confidence interval Hypothesis test Nonparametric test One way ANOVA Two way ANOVA Multiple comparison Chi-square test Correlation and univariate linear regression 6

7. Project(Fall, 2011) SAS – SAS codes demonstrated in class – SAS help session provided by the statistics department on Wednesdays. Project – Running topic: health, living style and happiness. – Survey based, include data collection, analysis, and report. – Focus on problem set up and explanation. 7

8. Challenges Motivation Teaching statistical concept and notation – Example 1 Example 1 Teaching application – Example 2 Example 2 Project design Attention 8

9. In the classroom Lecture focuses on statistical concepts Class activity – Monty hall – 17 points – Coke experiment – Hand-shaking experiment – Collaboration with labs? 9

10. Project Project design – Ultimate goal: hand on experience on experiment design, data collection, data analysis and result presentation Challenges – Skill set, timeline and monitoring – Experiment vs. observational study design – Software – Relevant/motivating topics ? Successful cases – Self-defined projects (sum 2008) – Instructor-defined projects Paper airplane contest Happiness and GPA Hotseat evaluation 10

11. Hotseat Introducing Hotseat on Spring, 2011 Role – As Clicker – As student support help session www.purdue.edu/hotseat/login/login.aspx More function development ? – Class question model Question edit Answer collection Result presentation – Class discussion model Student-initiated topic 11

12. Statistical consultant system Direct method selection through a logic flow. http://www.stat.purdue.edu/~tqin/statsys/sys tem101/system/main.htm http://www.stat.purdue.edu/~tqin/statsys/sys tem101/system/main.htm 12