1. DASI Session at DSI Austin, TX November Engaging Students and Making Statistics Meaningful for Business Majors
Mark L. Berenson, Montclair State University
“Teaching Business Statistics Courses Dedicated
to the Functional Area Disciplines”

2. Today’s “Typical” Student
Is very technologically savvy
Is woefully underprepared mathematically
Is not well-read
Has not learned to take notes
Has not learned to make connections
Has a very limited attention span
Is woefully underprepared mathematically with respect to arithmetic, logic, and algebraic skills.
Has not learned to make connections among courses, among topics, or among methods.

3. Questions to be Resolved
How can we work best with such underprepared and often uninterested students?
How do we get such students to think quantitatively to enhance their decision-making ability?
How do we get such students to appreciate the value of using statistics in their daily lives?
How do we get such students to have GRIT???

4. Students Need to be Motivated and Engaged to Succeed
We need to demonstrate why they should want to learn statistics
We need to provide data with applications that may be of interest to them
How it will help them think more critically.
Either in their intended discipline fields or based on current hobbies.

5. Enhance Student Motivation: Teach Discipline-Specific Courses
Quantitative Orientation:
Introductory Statistics for Finance
Introductory Statistics for Accounting
Introductory Statistics for Analytics
Non-Quantitative Orientation:
Introductory Statistics for Marketing
Introductory Statistics for Management
Textbooks will need to be developed to accommodate these discipline-specific courses. The texts will be much more concise, lower in price, and less likely to give both faculty and students a hernia to carry around.

6. Discipline-Specific Courses CONTENT
Topic Commonality:
Data Visualization and Descriptive Statistics
Simple Linear Regression
Introduction to Probability and Approach to Inference
Other topics are discipline specific.
All applications are discipline specific.

7. Discipline-Specific Courses GOALS
Foster Active Learning Through a Term Project :
Students work individually or on teams:
Finance: Each selects a company and a comparison of market performance is made among chosen companies.
Marketing: Each selects a marketing project with evaluation and critique from another
Improve Written and Oral Presentation Skills:
Students develop either individual or team project reports with classroom presentations.
I think it is important to assess student learning by having them articulate their findings.

8. Introductory Statistics for Finance
TOPICS
Review of fundamental mathematics for finance majors.
Data visualization through tables and charts with finance applications.
Numerical descriptive measures in finance (including the Sharpe ratio).
Introduction to index numbers with emphasis on the CPI-U and S&P 500 Index.
Descriptive statistics introduction to simple linear regression modeling with specific finance applications.
Resampling methods approach to statistical inference -- bootstrap percentile confidence interval estimation of investment measures and permutation testing for the slope.
Introduction to decision-making with applications in investing.
For CPI-U – its purpose, its development, its use as a price deflator, and its impact on labor-negotiated COLAs to salaries and wages.
For S&P 500 – its purpose and its development.
A study of the Beta coefficient, the Alpha coefficient and the Treynor ratio as measures of a company’s financial performance relative to the overall stock market.

9. Teaching Approaches Quantitative Disciplines: Finance, Accounting, Analytics
Develop concepts using formulas
Demonstrate algebraic connections
Use computer software for obtaining most results and for most data analysis

10. Introductory Statistics for Marketing
TOPICS
Review of fundamental mathematics for marketing majors.
Questionnaire Design and Sampling
Data visualization through tables and charts with marketing applications in Pivot Table drilldowns.
Brief introduction to probability through cross-classification tables.
Numerical descriptive measures in marketing.
Normal Distribution, Sampling Distributions of and P, and C.L.T.
Classical approach to statistical inference using marketing applications -- confidence interval estimation for µ and П, comparison of two means and two proportions, comparison of multiple means and multiple proportions.
Simple linear regression modeling (descriptive and inferential) with marketing applications.
The following are suggested topics – but the teaching of the topics should be very different from the teaching of the quantitatively oriented discipline courses.

11. Teaching Approaches Non-Quantitative Disciplines: Marketing or Management
Stress concepts through definitions
Minimize use of symbols, formulas, and algebraic expressions
Use computer software for obtaining all results and for all data analysis

12. Teaching Approaches Other Disciplines (IT, IB) or Undecided
Teach traditional “general” business statistics course
BUT
Stress concepts through definitions
Minimize use of symbols, formulas, and algebraic expressions
Use computer software for obtaining all results and for all data analysis

13. Force Student Engagement in Non-Quantitative Discipline Courses: “Flip” the Classroom
Make students accountable and responsible for their own learning.
Become the coach and facilitator to guide their learning.
Give students confidence they can learn on their own throughout their lives.
For a student audience that is mathematically underprepared, that is basically uninterested in learning, that doesn’t know how to take notes and who doesn’t want to hear lectures because they are so quickly distracted, consider flipping the classroom to force engagement as I am currently doing.