Course Summary
Credit Type:
Organization's ID:
40 hours (self-paced)
Dates Offered:
Credit Recommendation & Competencies
Level Credits (SH) Subject
Lower-Division Baccalaureate 3 Elementary Statistics, Introduction to Statistics, or Introduction to Business Statistics


The course objective is to survey quantitative methods (QM), or the application of statistics in the workplace. Examines techniques for gathering, analyzing, and interpreting data in any number of fields - from anthropology to hedge fund management.

Learning Outcomes:

  • Define and apply the following terms: data sets, mean, median, mode, standard deviation, and variance
  • Summarize and interpret data in a tabular format using frequency distributions and visually with histograms
  • Define and apply the concept of a probability distribution, and explain the properties of different distributions
  • Relate the central limit theorem to sample size and normal distribution
  • Estimate intervals over which the population parameter could exist using sample data
  • Identify the dependent and independent variables in the linear regression model
  • Work with statistical data in a spreadsheet environment
  • Explain the importance of statistics to business
  • Explain the differences between quantitative and qualitative data, and identify examples of each type of data
  • Differentiate between discrete and continuous probability distributions
  • Define and apply the concept of a random variable, and differentiate the population from a sample
  • Describe and identify the different sampling methods, including systematic, stratified random, cluster, convenience, panel, and quota sampling, and identify examples of each
  • Use a point estimator from a sample to estimate the entire population
  • Apply hypothesis testing for testing population parameters using one or two samples
  • Plot a regression line, and explain how the regression coefficient shapes that line

General Topics:

  • An introduction to statistical analysis
  • Counting, probability, and probability distributions
  • The normal distribution
  • Sampling and sampling distributions
  • Estimation and hypothesis testing
  • Correlation and regression
Instruction & Assessment

Instructional Strategies:

  • Classroom Exercise
  • Computer Based Training
  • Practical Exercises

Methods of Assessment:

  • Examinations

Minimum Passing Score:

Supplemental Materials