Course Description
Explores methods of collecting, analyzing and interpreting data for managerial decision making. Includes data presentation, measures of central tendency, dispersion, and skewness; discrete and continuous probability distributions; sampling methods and sampling distributions; and confidence interval estimation of parameters and tests of hypotheses.
Course Objectives
- Present data, calculate and interpret measures of central tendency and dispersion, and interpret these meanings
- Solve problems involving elementary probabilities and interpret their results
- Identify and use various types of probability distributions to solve relevant problems
- Use sampling distributions to construct confidence intervals and estimates of population parameters
- Test statistical hypotheses using the z and t distributions
- Develop and evaluate statistical applications in quality and productivity management
Week 1
Lecture: Introduction
Lecture: Definition and Terms
Lecture: Organizing Numeric Data
Lecture: Tabulating and Graphing Categorical Data
Outcomes
- Present data, calculate, and interpret measures of central tendency and dispersion, and interpret these meanings
- Solve problems involving elementary probabilities and interpret their results
- Identify and use various types of probability distributions to solve relevant problems
- Use sampling distributions to construct confidence intervals and estimates of population parameters
- Test statistical hypotheses using the z and t distributions
- Develop and evaluate statistical applications in quality and productivity management
Week 2
Lecture: Descriptive Data Summaries and Measures of Central Tendency
Lecture: Measures of Variation
Week 3
Lecture: Probability and Boolean Concepts
Lecture: Counting
Week 4
Lecture: Discrete Probability
Week 5
Lecture: Continuous Probability
Lecture: Sampling Distributions
Week 6
Lecture: Confidence Intervals
Week 7
Lecture: Hypothesis Testing—Part 1
Lecture: Hypothesis Testing—Part 2
Week 8
Lecture: Integrated Quality and Process Management
The course description, objectives and learning outcomes are subject to change without notice based on enhancements made to the course. October 2013
