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

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

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

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

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

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

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

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

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

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. 393-397 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