Redesign of OPRE 202: Statistical Data Analysis By Gisela Bardossy, Ph.D. Assistant Professor of Decision Science, Merrick School of Business

Outline Course background: Second course in statistics, mainly inferential statistics, Excel is the main tool Main concern: High DFW Rate ~30% Exploration of students’ records: Understand students at risk Fall 2017 Initiatives Spring 2018 Updates

5 Years in OPRE 202 Number of Students 2564 Day 40.29% 1033 Evening 21.88% 561 Online 37.83% 970 Number of Sessions 65 38.46% 25 20.00% 13 41.54% 27 Number of Faculty 14 Average Number of Sessions per Faculty 4.64 Min 1 Max 9 Mode 4

High DFW Rate 31.36% Drops with out a W

DFW Rate ~30% 24% 32% 40% 26% 35% 28% 31%

Freshmen have the highest W Worst 64% Best 28%

Part-time students show highest DFW rate 36% 31%

Low GPA students 100% 72% 46%

Time of Enrollment in the Class

Findings: 14 different instructors in the last 5 years The DFW rate (which also includes students that drop without a grade) seems persistent over time at around 30%. DFW rate is worst among students with less than 30 credits (freshmen), 65%. Students enrolled in 13 credits or less also have the highest rate of DFW. 72% of students with low GPA (under 2) drop or fail the course while 46% of students do with GPA below 2.49. The DFW rate does not change across time of enrollment but the rate of F increases for students that add one week or after the start.

Who struggles in the course? Freshmen Part-time students Low GPA students

Fall 2017 - Initiatives Course content: Student support: Streamline content. More time spent on foundation (review concepts from basic statistics) Student support: Course preparation workshops Early Alert system Weekly SI sessions: student lead work sessions MyStatLab for Homework Sets Four in-class exams Semester long projects with partial submissions: data collection, analysis, report and presentation

Fall 2017 - Results No data yet from Records ~ 16% DFW for one section

Spring 2018 - Update Course content: Student support: Streamline content. More time spent on foundation (review concepts from basic statistics) Student support: Course preparation workshops Early Alert system Weekly SI sessions: student lead work sessions MyStatLab for Homework Sets Four in-class exams Weekly short quizzes + Midterm & Final Exam Semester long projects with partial submissions: data collection, analysis, report and presentation

Gisela Bardossy mbardossy@ubalt.edu Thank you! Gisela Bardossy mbardossy@ubalt.edu

Semester Long Project Business Idea Descriptive Statistics: Analyze BNIA (Baltimore Neighborhood Indicator Alliance) to decide a location for your business One sample hypothesis test: Pose a business decision question that you could address using one-sample hypothesis testing. Multiple sample hypothesis test: Pose a business decision question for multiple sample hypothesis testing. Regression Analysis: Develop a regression model relevant for your business.