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Wisconsin School of Business

Intro to Business Analytics - Quantitative Methods

Available dates

On demand
USD 895


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About the course

Analysis of quantitative information is important to any business problem, and especially so for Six Sigma projects. This online course gives participants the knowledge and the tools to dissect complicated business problems and provide quantitative analysis to problems instead of relying on intuition and instincts. Part of the course involves role play in which the learner is assigned to be a consultant to a multifaceted resort hotel business. Step by step, this multimedia program gives the participant the knowledge and tools needed to satisfy the hotel manager's demands for information and analysis. Most learners complete the program in approximately 20 to 30 hours, depending on the number of problems performed and previous experience with the topics discussed.

How You Will Benefit

  • Develop a solid understanding of the basic concepts underlying quantitative analysis and business statistics
  • Strengthen your ability to frame and formulate management decision problems
  • Interpret and evaluate data that relates to business and process improvement problems
  • Use a variety of Microsoft Excel functions, charts, and tests to analyze business data


Unit 1: Introduction to Course Learning System

  • Course philosophy
  • Introduction to story line and characters
  • Your role as advisor/consultant to the business owner
  • Navigating through the course management system
  • Accessing course resources (data files, glossary, pre-test, post-test)

Unit 2: Descriptive Statistics

  • Working with data (graphs, interpretation)
  • Measures of “central tendency” (mean, median, mode)
  • Variability (variance, standard deviation, coefficient of variation)
  • Relationships between variables (correlation, scatter diagrams)

Unit 3: Sampling and Estimation

  • Generating random samples
  • The normal distribution
  • The central limit theorem
  • Confidence intervals for sample means, sample proportions

Unit 4: Hypothesis Testing

  • Hypothesis tests for single population means, proportions
  • Using P-values
  • Hypothesis tests comparing two population means, proportions

Unit 5: Regression

  • The uses of regression
  • Calculating the regression line
  • Goodness of fit measures
  • Residual analysis
  • Coefficient significance

Unit 6: Multiple Regression

  • Introduction to multiple regression
  • Interpretation of coefficients, R2, residuals
  • Multicollinearity
  • Lagged variables
  • Dummy variables

Note that Units 7 and 8 are not required for course completion but provided for the student.

Unit 7: Decision Analysis 1 (not required for course completion)

  • Introduction to probability
  • Decision trees
  • Expected monetary value (EMV)
  • Sensitivity analysis

Unit 8: Decision Analysis 2 (not required for course completion)

  • Joint, conditional, and marginal probabilities
  • The expected value of information
  • Risk analysis


FIRST DAY - Includes breakfast, lunch, breaks and dinner

  • Check-In and Breakfast 7:30 a.m. - 8:15 a.m.
  • Course 8:15 a.m. - 5 p.m.
  • Dinner 4:30 p.m. - 10 p.m.

LAST DAY - Includes breakfast, lunch and breaks

Breakfast 7:30 a.m. - 8:15 a.m.

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