You will be able to perform a multiple regression analysis using real-world data working on a real-world business problem.
You will be able to make a confident revenues forecast.
You will gain an appreciation of the information required to make such a forecast, forecasting methodologies, and the strength and weaknesses of such forecasts.
Referencing modules: Forecasting Project
You understand the goals, structures, and procedures for learning in BUS 619.
Referencing modules: Syllabus
Assessed by: Statistics Self Test
Understand the purpose and objectives of Business Statistics and Analytics, how it is organized, and learn about the basics of working with data.
Referencing modules: Overview of Business Analytics
Assessed by: Session 1 Exercises
Referencing modules: Residual Analysis
Assessed by: Session 10 Exercises
After this module you should be able to:
Referencing modules: Model Building
Assessed by: Session 11 Exercises
Understand visual and statistical anaytics for describing categorial data. Key concepts: categorial data as groups, qualitative distribution, one-way tables, bar chart, pie chart, pareto chart, mode, discreet probability, conditional probability, two-way tables, emperical vs. a priori probability, excpected value, payoff matrix, decision tree
Referencing modules: Categorical Data
Assessed by: Session 2 Exercises
Understand visual and statistical analytics for describing numerical data. Key concepts: numerical data as measures, quantitative distribution, histogram, box plot, distribution central tendency, variability, shape, bi-variate data, correlation
Referencing modules: Numerical Data
Assessed by: Session 2 Exercises
Understand describing time series data, naive time series forecasting, Forecasting project Part 1
Referencing modules: Time Series Data
Assessed by: Session 4 Exercises
Understand working with emperical and a priori distributions as data models and inferences from sample data, outliers, and emperical validaton of Normal distibution assumption.
Referencing modules: Working with Distributions
Assessed by: Session 5 Exercises
The student will be able to identify data and apply appropriate confidence interval estimates and hypothesis testing based on need and data type using methods as indicated in Choosing Situation by Data Type.
Referencing modules: Basics of Inferential Statistics
Assessed by: Session 7 Exercises
After completing this module you will:
Referencing modules: ANOVA
Assessed by: Session 8 Exercises
After this module you should be able to:
Referencing modules: Simple Linear Regression
Assessed by: Session 9 Exercises
Obtain a Six Sigma White Belt Certification.
Referencing modules: Six Sigma Certification
Assessed by: Six Sigma Exercises
Understand fundamental economics reasoning and concepts common to Masters coursework and how they apply to business problems and how to implement them in a spreadsheet for quantitative analysis.
Referencing modules: Tutorials
Assessed by: Masters Econ Tutorial
Obtain or refresh fundamental spreadsheet skills needed for your courses and for business Understand how to construct a structured spreadsheet models that are ready for performing and communicating quantitative analysis.
Referencing modules: Tutorials
Assessed by: Masters Excel Tutorial
Obtain or relearn fundamental quantitative reasoning and math concepts and how to apply them within spreadsheets to perform quantitative analysis useful in business.
Referencing modules: Tutorials
Assessed by: Masters Math Tutorial
After this module you will understand:
What control charts are and how they relate to process quality management
How to identify different control charts and when they apply
Statistical basis for in-control or out of control processess
Recognizing common out of control patterns
Referencing modules: Statistical Process Control
Assessed by: Session 6 Exercises