Student Projects in Statistics GCTM Conference October 14, 2010 Dianna Spence NGCSU Math/CS Dept, Dahlonega, GA

Background: NSF Grants The material shared in this presentation is the product of work supported by 2 NSF Grants. Phase I Grant ( ) “Authentic, Career-Specific Discovery Learning Projects in Introductory Statistics”  Developed and pilot tested curriculum materials to facilitate discovery projects in statistics  Measured 3 specific student outcomes Phase II Grant ( ) “Discovery Learning Projects in Introductory Statistics”  Refine & improve materials  Pilot test nationally  Improve assessment of outcomes

Website Resources What’s on this website? This presentation NSF Main Project Information Page Phase I Instructional Materials (OLD) Phase II Instructional Materials  These will be posted as they are developed over the next year

Types of Projects Linear regression* Chi-squared tests * Part of NSF supported work t-tests*  Designs 1-Sample 2 Independent samples 2 Dependent samples

Project Tasks for Students Identifying research questions Defining specific variables Data collection  Finding sources of data Designing surveys if applicable  Identifying & implementing a sampling strategy Organizing and recording data Appropriate analysis of data Interpretation of results Reporting results (written and oral)

Today’s Focal Points Where can students get authentic data? What kinds of research questions do students investigate? How are student outcomes measured?  Evaluation of student work  Assessing the benefit of projects/materials  Improving our instruments and findings

Collecting Data: 3 Categories Administer surveys  Primary focus of Phase I materials  Makes survey design an element of the project Find data on the Internet Physically go out and record data e.g., measure items, time events with a stopwatch, look at prices, look at nutrition labels

Internet Data Sources I. Government/Community Census Bureau: Georgia Statistics System: City Data Site: Bureau of Justice Statistics: Georgia Dep’t. of Education reporting page: Georgia Tax Assessors:

Internet Data Sources II. Restaurants: Nutrition Info Applebees: Arby’s: Burger King: utritionInformation.pdf utritionInformation.pdf McDonalds: Ruby Tuesday’s: Student’s favorite place to eat?

Internet Data Sources III. Sports Data Sports Statistics Data Resources (Gateway) Data Resources/ Data Resources/ NFL Historical Stats: Individual team sites

Internet Data Sources IV. Retail/Consumer (General) Cost/Prices Consumer Report ratings. Product Specifications  e.g., size measurements, time/speed measurements, MPG for cars

Sample Student Projects One Sample t-Test:  1-tailed: H a predicting that the average purebred Boston Terrier puppy in the U.S. costs more than $500  Stratified sample representing different regions of the country  t statistic =1.73  P value=  Conclusion: Evidence at 0.05 significance level that on average, purebred Boston Terrier puppies are priced higher than $ in the U.S.

Sample Student Projects Matched Pairs t-Test:  1-tailed: H a predicting on average, Wal-Mart prices would be lower than Target prices for identical items  t statistic =.4429  P value=  Conclusion: Mean price difference not significant; insufficient evidence that Wal-Mart prices are lower Item WalMart Target 64-oz. Mott’s Juice oz LeSeur Peas

Sample Student Projects Matched Pairs t-Test:  2-tailed: H a predicting that on average, students’ rating of Coke and Pepsi would be different.  t statistic =2.62  P value= (2-tailed)  Conclusion: Evidence that on average, students rated the two drinks differently (Coke was rated higher) Participant Coke Pepsi #1 89 #

Sample Student Projects t-Test for 2 independent samples:  1-tailed: H a predicting that on average fruit drinks have higher sugar content per ounce than fruit juices  t statistic =  P value=  Conclusion: Sample data did not support H a. No evidence that on average, fruit drinks have more sugar than fruit juices.

Sample Student Projects t-Test for 2 independent samples:  1-tailed: H a predicting that in local state parks, oak trees have greater circumference than pine trees on average  t statistic = 4.78  P value= 7.91 x 10 –6  Conclusion: Strong evidence that in local state parks oak trees are bigger than pine trees on average.  Lurking variable identified and discussed: age of trees (and possible reasons that oak trees were older)

Sample Student Projects

Online Resource: Materials for Students (OLD) Student Guide  Overall Project Guide Help for each project phase  Technology Guide  Variables and Constructs

Online Resource: Instructional Materials (OLD) Instructor Guide  Project overview Timelines Implementation tips Best practices  Handouts for different project phases  Evaluation rubrics  Links to student resources

Assessment Scoring Rubrics  Advantages Consistency Manageability Communicate expectations  Encompass All Project Components Grade milestones along the way  Resources for Rubrics

Phase I Assessment of Outcomes Varied by Instructor Overall results given here Instrument  Perceived Usefulness Pretest: Posttest: Significance: p =  Self-Beliefs for Statistics Pretest: Posttest: Significance: p = 0.032**  Content Knowledge Pretest: 6.78 Posttest:7.21 Significance: p = 0.088*

Multivariate Analysis: Content Knowledge

Multivariate Analysis: Statistics Self-Efficacy

Qualitative Findings: Student Feedback Student Quotes Shared by Instructors “The main thing that we have learned is that statistics take time. They cannot be conjured up by a few formulas in a few minutes. The time and effort that is put into a small research project such as this is significant. On a large scale, one can quickly understand the kind of commitment of money and time that is required just to obtain reasonable data.” “While our results did not meet our initial expectations, this is not an utter disappointment. Before this project, statistics looked simple enough for anyone to sit down and do, but now it is evident that it requires more creativity and critical thinking than initially expected. Overall, it was an edifying experience.”

Improving Our Assessments Perceived Usefulness  Reduce/eliminate focus on career Content Knowledge  Add questions to reflect what student knows about conducting research Data collection methods Sampling strategies Organizing and analyzing data

Website Resources What’s on this website? This presentation NSF Main Project Information Page Phase I Instructional Materials (OLD) Phase II Instructional Materials  These will be posted as they are developed over the next year