1. What Statistical Knowledge Should Students Know to Prepare for Graduate Business Analytics?
David M. Levine,
Baruch College (CUNY)
Decision Sciences Institute Meeting,
Data, Analytics, Statistics Instruction Mini-Conference
November 25,2017

2. Advancing the Connection Between Industry and Statistics Education
Analytics has made statistical thinking critical for students
Statistics courses need to adjust to this new environment
Analytical skills are more important than arithmetic skills
Using software maximizes the importance of analytical skills
Decision Sciences Institute Meeting,
Data, Analytics, Statistics Instruction Mini-Conference November 25,2017

3. Decision Sciences Institute Meeting,
Technology and the Business Statistics Course
Business statistics courses need to use software that will be available on students’ jobs
when they graduate.
The software most appropriate for an introductory course is Microsoft Excel
(currently used in about 80% of introductory business statistics courses).
Using an add-in may assist in learning to use Excel for statistics.
More advanced business statistics courses that focus on analytics may combine Excel
with statistical software such as JMP.
Decision Sciences Institute Meeting,
Data, Analytics, Statistics Instruction Mini-Conference November 25,2017

4. Employers Demand the Ability to Make Data Based Decisions
Statistics as a way of thinking and problem-solving. Use a problem- solving framework such as DCOVA (see References 1 - 5):
Define your business objective and the variables for which you want to reach conclusions
Collect the data from appropriate sources
Organize the data collected
Visualize the data by constructing charts
Analyze the data to reach conclusions and present those results
and
Communicate your results
Decision Sciences Institute Meeting, Data, Analytics, Statistics Instruction Mini-Conference November 25,2017

5. The Typical Introductory Business Statistics Course
Overview/orientation
Tables and Charts/Descriptive Statistics
Probability and Probability Distributions
Confidence Intervals and Hypothesis Testing
Regression
Decision Sciences Institute Meeting,
Data, Analytics, Statistics Instruction Mini-Conference November 25,2017

6. Decision Sciences Institute Meeting,
Tell A Story
Each example should tell a story
Focus on an application from a functional area of business – accounting, eco/finance, management, marketing, information systems
For every story, use the DCOVA steps of Define, Collect, Organize, Visualize, and Analyze and Communicate
Decision Sciences Institute Meeting,
Data, Analytics, Statistics Instruction Mini-Conference November 25,2017

7. Decision Sciences Institute Meeting,
What to Deemphasize?
Reduce Probability: no more than 30 minutes to define terms
Reduce Probability distributions: cover only the normal distribution
Reduce Hypothesis Testing: cover only basic concepts, difference between means, difference between proportions (needed in A-B testing common in online presentation systems), p-values
Decision Sciences Institute Meeting,
Data, Analytics, Statistics Instruction Mini-Conference November 25,2017

8. Decision Sciences Institute Meeting,
What to Add?
Organizing and Visualizing Data
Multiway contingency tables
Drilling down/Excel slicers
Scatterplots and sparklines
Other visualizations
Predictive Analytics
Coverage of additional topics in simple linear regression and introduction to multiple regression
Logistic regression and classification and regression trees (not possible in one-semester course – save for the analytics course)
Decision Sciences Institute Meeting,
Data, Analytics, Statistics Instruction Mini-Conference November 25,2017

9. Regression
Critically important to cover because of its use in analytics
Begin with a business problem of trying to predict the value of a variable of interest. Then ask what other variables might be useful in helping to predict the value of the variable of interest.
Do this before going through any computations.
Review the meaning of the Y intercept and the slope.
Don’t do the proof of the Least squares method.
Focus on interpreting the results of software not on doing computations
Make sure to mention the assumptions and what happens if the assumptions are violated.
Discuss residual analysis.
Decision Sciences Institute Meeting, Data, Analytics, Statistics Instruction Mini-Conference November 25,2017

10. Decision Sciences Institute Meeting,
References
Berenson, M. L., D. M. Levine, and K. A. Szabat, Basic Business Statistics 14th Ed., (Boston, MA.: Pearson Education, 2019) forthcoming
Levine, D. M. and D. F. Stephan, “Teaching Introductory Business Statistics Using the DCOVA Framework”, Decision Sciences Journal of Innovative Education, Vol. 9, September 2011, pp
Levine, D. M., D. F. Stephan, and K.A. Szabat, Business Analytics (Boston, MA.: Pearson Education, 2019) forthcoming
Levine, D. M., D. F. Stephan, and K.A. Szabat, Statistics for Managers Using Microsoft Excel, 8th Ed., (Boston, MA.: Pearson Education, 2017)
Levine, D. M., K. A. Szabat , and D. F. Stephan, Business Statistics: A First Course, 7th Ed., (Boston, MA.: Pearson Education, 2016)
Decision Sciences Institute Meeting,
Data, Analytics, Statistics Instruction Mini-Conference November 25,2017