Data and Decision Analysis for Engineering

Business and engineering management decisions are made with limited data set and partial information in uncertain environments. Therefore, statistical data and decision analysis is required to translate raw data into meaningful information that is relevant to business and/or engineering decision-making (e.g., quality control, product sampling, profit maximization, cost minimization, optimal decision strategy, etc.). The objectives of this course are first to give students a practical and an intuitive understanding of probability and statistics. And then to illustrate how to apply probabilistic methods and decision analysis to make rational and statistically optimal management decisions in the face of uncertainty and based on partial information. In order to achieve the objectives in this course we first develop a foundation of probability and statistics and then utilize Microsoft Excel to master some fundamentals of data visualization, decision analysis, statistical inference, estimation, prediction, confidence interval, and hypothesis testing. The focus will always be on intuition rather than mathematical notation. Topics will also be applied in management settings and practical examples will be discussed to build the bridge between theoretical models and the real world