工程統計

臺北科技大學 115-1 學期課程，課號 360772。

課程大綱

本課程旨在介紹工程統計學的基本理論與應用，內容涵蓋描述統計、機率理論、隨機變數與機率分佈、抽樣分配、參數估計、信賴區間、假設檢定、迴歸分析、可靠度分析及工程數據分析方法。課程將透過數學推導、習題演練及工程案例說明統計方法之原理與應用。此外，學生將使用 Python 進行資料分析、統計模擬與蒙地卡羅模擬，並完成統計分析專題，以培養解決工程問題及數據分析之能力。 This course introduces the fundamental principles and applications of Engineering Statistics. Topics include descriptive statistics, probability theory, random variables and probability distributions, sampling distributions, parameter estimation, confidence intervals, hypothesis testing, regression analysis, reliability analysis, and engineering data analytics. Mathematical derivations, problem-solving exercises, and engineering case studies will be used to develop students' understanding of statistical methods. In addition, students will utilize Python for data analysis, statistical simulation, and Monte Carlo methods, culminating in a coding project that applies statistical techniques to real-world engineering problems.

課程進度

Week 1: Introduction to Statistics and Data Visualization Week 2: Descriptive Statistics and Measures of Variability Week 3: Probability Concepts and Counting Methods Week 4: Random Variables and Probability Distributions Week 5: Discrete Probability Distributions Week 6: Continuous Probability Distributions Week 7: Sampling Distributions and Central Limit Theorem Week 8: Midterm Examination Week 9: Statistical Estimation and Confidence Intervals Week 10: Hypothesis Testing Fundamentals Week 11: Comparison of Means and Analysis of Variance (ANOVA) Week 12: Correlation and Simple Linear Regression Week 13: Multiple Regression and Model Assessment Week 14: Statistical Quality Control and Process Capability Week 15: Reliability Analysis and Engineering Applications Week 16: Final Examination and Final Project Presentation Weeks 17–18: Self Learning (Online Learning, Python Coding Project Development, and Final Report Submission)

評量方式

Weekly assignments: 5% Midterm exam: 30% Group project and presentation: 40%

教材

【遵守智慧財產權觀念，請使用正版教科書，不得使用非法影印教科書】 使用外文原文書：是 Ross, Sheldon M. Introduction to probability and statistics for engineers and scientists. Academic press, 2020.