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 1/2-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
