Course Descriptions:
Applied Data Analysis - 3 credits
10196180
This course provides the student with the tools and skills to collect and analyze data allowing them to solve problems and improve processes. An emphasis will be placed on the use of statistical techniques to create and implement a data collection plan. Statistical techniques emphasized will be process mapping, failure mode and effects analysis, probability, confidence intervals, measurement systems analysis, and hypothesis testing. Prerequisite: Introductory Statistics 10804189
Project Management - 3 credits
10196188
The learner applies the skills and tools necessary to design, implement, and evaluate formal projects. Each learner will write a project proposal, work with project teams, sequence project tasks, develop project budgets, identify project resources, implement the project, chart project progress, deal with variations, evaluate the project, and use various technology in these processes.
Team Building & Problem Solving - 3 credits
10196189
The learner applies the skills and tools necessary to facilitate problem solving in a team environment. Each learner will assume the roles and responsibilities of team leadership in the stages of team development, use a systematic problem solving process and employ consensus building and conflict management strategies.
Managing for Quality - 3 credits
10196192
The learner applies the skills and tools necessary to implement and maintain a continuous improvement environment. Each learner will demonstrate the application of a personal philosophy of quality, identify stakeholder relationships, identify ways to meet/exceed customer expectations, apply a systems-focused approach, use quality models and tools, manage a quality improvement project, and measure effectiveness of continuous improvement activities.
Introductory Statistics - 3 credits
10804189
Students taking Intro Statistics display data with graphs, describe distributions with numbers perform correlation and regression analyses, and design experiments. They use probability and distributions to make predictions, estimate parameters, and test hypotheses. They draw inferences about relationships including ANOVA.
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