1. ‘The’ Second Course in Statistics
Robin Lock, Burry Professor of Statistics
St. Lawrence University,
Dick De Veaux, Williams College
Breakout Session at USCOTS07

2. Positioning the “Second” Course
(in the “good old days”)
Calculus I
Calculus II
Calculus III
Intro Stat
Linear Alg.
Probability
Math Stat

3. Current Consensus Intro Stat ? ? ? ? ? AP Stat
GAISE:
AP:
What (could be, should be, might be, is) the (or a) second course in statistics?

4. MultiVariable Calculus
Mathematics
Proofs
One Variable Calculus
MultiVariable Calculus
Linear Alg.
Discrete
Diff. Eq’s

5. Economics Financial Micro Intro Industrial Economics Macro Labor
Public

6. Chemistry
General
Organic
Physical

7. Psychology Behavioral I Developmental N T Social R O Physiological
Abnormal

8. Borrowing from Other Disciplines
Math: In the second course, repeat the topics in the first course in a multivariable setting
Stat: Multiple regression, multi-factor ANOVA, …
Economics: Have two main second courses that build on the ideas of the first course
Stat: Experimental Design & Applied Regression

9. Borrowing from Other Disciplines
Chemistry: Develop a single sequence
Stat: Might require redesign of intro
Psychology: Have lots of “second” courses that expand on different aspects of the first course.
Stat: Experimental Design, Sampling, Applied Regression, Nonparametric Methods, Categorical

10. = + = + Unique to Statistics Modeling approach: Data Model Error
Response Variable =
F(Predictors & Explanatory factors) +
“Unexplained” Variability

11. Categorical vs. Quantitative Approach
Predictor(s)
Quantitative
Categorical
Quantitative
Multiple Regression
Multifactor ANOVA
Response
Logistic Regression
Loglinear Models
Categorical

12. Data Production Approach
Experimental Design
Expand on designs from intro
Randomized, factorial, block, …
Analyzing designed data
Sampling
Beyond the SRS
Cluster, stratified, …
Estimates based on sample method

13. What if the Standard Method Doesn’t Work? Approach
Data not normal?
Nonparametric methods
Bootstrap CI’s and Permutation Tests
Transformations
Errors not independent?
Time series analysis

14. Questions? How do we attract students to take Stat II?
What should we assume from Stat I?
What about software/technology?
Can we still use activities and explorations?
Do we have to assume more math background?
Is there a good textbook?
What will students do after Stat II?

15. Create Your Own Stat II
Divide into groups - perhaps by similar institutions or ideas for a second course
Develop a syllabus for a second course – by consensus or with minority reports
Assume A GAISE compliant Stat I
Prepare to report back to the rest of the group.