PART I: CAPSTONE EXPERIENCES

1. PREPARING DATA FOR ANALYSIS

Computing Concepts and Procedures: Coding Protocol, Data Editing, Data Entry, SAS PROC COMPARE / Mathematical Concepts: None / Statistical Concepts: Five-Number Summary, Frequency Table, Scatter Plot, Systematic Random Sample / Materials Required: None

2. DESIGNING A TELEPHONE SURVEY

Computing Concepts and Procedures: Data Entry Computer Screen / Mathematical Concepts: None / Statistical Concepts: Data Recording Form, Survey Instrument / Materials Required: None

3. DETERMINING THE SAMPLE SIZE

Computing Concepts and Procedures: Noncentral t Distribution Function, Numerical Search, SAS Function GAMMA, SAS Function PROBT, SAS Function TINV, Student''s t Distribution Probability Point / Mathematical Concepts: Gamma Function, Nonlinear Inequality / Statistical Concepts: Confidence Interval, Expected Value, Function of a Random Variable, Hypothesis Test, Power of a Test, Non-Central t Distribution, Student''s t Distribution / Materials Needed: None

4. DESIGNING AN EXPERIMENT TO COMPARE TWO HORN ACTIVATION BUTTONS

Computing Concepts and Procedures: Random Number Generation, SAS Function PROBT, Two-Dimensional Plot / Mathematical Concepts: Derivative, Inverse Function / Statistical Concepts: Change of Variable, Density Function, Dependent Sample Design, Independent Sample Design, Normality Assumption, Power of a Test, Comparing Two Treatments / Materials Required: None

5. USING REGRESSION TO PREDICT THE WEIGHT OF ROCKS

Computing Concepts and Procedures: SAS PROC PLOT, SAS PROC PRINT, SAS PROC REG, Two-Dimensional Plot / Mathematical Concepts: Ellipsoid, Rectangular Solid / Statistical Concepts: Regression, Residual, R-Square, Scatter Plot / Materials Required: For each team, a caliper capable of measuring to the nearest 0.01 inch, a scale capable of measuring to the nearest gram, 20 rocks of various sizes but of similar composition, and muffin pans with holes numbered from 1 to 20. The rocks must have dimensions and weights within caliper and scale capacities

6. ESTIMATING VARIANCE COMPONENTS IN TACK MEASUREMENTS

Computing Concepts and Procedures: SAS PROC VARCOMP / Mathematical Concepts: System of Linear Equations / Statistical Concepts: Analysis of Variance, Factorial Design, Nested Design, Random Effect, Replicate, Unbiased Estimator, Variance Component / Materials Required: For each team, 4 nominal ½-inch carpet tacks, 3 micrometers capable of measuring to .001 inch, 2 objects with a premeasured dimension of less than 1 inch, 12-inch length of masking tape

7. CLASSIFYING PLANT LEAVES

Computing Concepts and Procedures: SAS PROC DISCRIM, Two-Dimensional Plot / Mathematical Concepts: Linear Inequality, Matrix Operations / Statistical Concepts: Bivariate Normal Distribution, Classification, Density Function, Discriminant Analysis, Scatter Plot, Unbiased Estimator / Materials Required: For each team, a ruler marked in millimeters

8. USING A RESPONSE SURFACE TO OPTIMIZE PRODUCT PERFORMANCE

Computing Concepts and Procedures: SAS PROC GLM, SAS PROC REG, Three-Dimensional Plot / Mathematical Concepts: Maximization, Quadratic Surface, System of Linear Equations / Statistical Concepts: Experimental Design, Factor Selection, Multiple Regression, Randomization, Response Surface / Materials Required: For each team, a balsa wood airplane with moveable wings, a ruler, 4 paper clips, and a 50-foot measuring tape

9. MODELING BREAKING STRENGTH WITH DICHOTOMOUS DATA

Computing Concepts and Procedures: Programming Newton''s Method, SAS PROC LOGISTIC / Mathematical Concepts: Maximization, Newton''s Method, Partial Derivative, System of Non-Linear Equations / Statistical Concepts: Bernoulli Trial, Dichotomous Data, Goodness of Fit, Likelihood Function, Likelihood Ratio Test, Logistic Distribution, Logistic Regression, Maximum Likelihood Estimation, Scatter Plot / Materials Required: For each team, 99 two-ply facial tissues with a minimum dimension of at least 8 inches, two 7-inch embroidery hoops, three full 12-ounce soft drink cans, a ruler marked in centimeters, and a 1-ounce egg-shaped fishing weight

10. ESTIMATING VOTER PREFERENCES

Computing Concepts and Procedures: Random Number Generation, SAS PROC SORT / Mathematical Concepts: Minimization Subject to an Equality Constraint / Statistical Concepts: Population Proportion, Sample Size Allocation, Sampling Error, Simple Random Sample, Stratified Random Sample, Standard Error / Materials Required: None

11. ESTIMATING THE PROBABILITY OF A HIT IN BASEBALL

Computing Concepts and Procedures: Two-Dimensional Plot / Mathematical Concepts: Integration, Non-Linear Inequality / Statistical Concepts: Bias, Bayesian Estimation, Bernoulli Trial, Binomial Distribution, Beta Distribution, Maximum Likelihood Estimation, Mean Squared Error, Method of Moments, Minimum Variance Unbiased Estimation, Squared Error Loss / Materials Required: None

PART II: SHARPENING NON-STATISTICAL SKILLS

12. STRATEGIES FOR EFFECTIVE WRITTEN REPORTS

13. STRATEGIES FOR EFFECTIVE ORAL PRESENTATIONS

14. PRODUCING VISUAL AIDS WITH POWERPOINT

15. STRATEGIES FOR EFFECTIVE CONSULTING

16. STRATEGIES FOR FINDING A JOB

INDEX