Đang tải... (xem toàn văn)
ENGINEERING SYSTEMS & DECISION ANALYSIS (CIVE3066) COURSE INTRODUCTION Instructor Nguyen Tuan Thanh LE (thanhlnt@tlu edu vn) Based on the CIVE203 Engineering system and decision analysis Colorado stat[.]
ENGINEERING SYSTEMS & DECISION ANALYSIS (CIVE3066) COURSE INTRODUCTION Instructor: Nguyen-Tuan-Thanh LE (thanhlnt@tlu.edu.vn) Based on the CIVE203 - Engineering system and decision analysis - Colorado state University, USA & Role of statistics in engineering – California State University, USA COURSE OBJECTIVES ▪ Prepare you to effectively use models and statistics in your courses and career using MatLab/Octave and GIS skills ▪ Provide you with the capabilities of: ▪ Understanding the concepts of mathematical modeling and statistical data analysis as ▪ ▪ ▪ ▪ applied to civil engineering systems Estimating parameters for various statistical distributions, determining which distribution best describes a set of data and to generate random samples from those distributions Demonstrating the proper application of confidence limits and hypothesis testing to examples from civil engineering systems Demonstrating the proper application of simple linear or multiple regression for building empirical models of engineering and scientific data Demonstrating the use of Geographic Information Systems (GIS) for spatial data collection, organization, and analysis COURSE INSTRUCTORS ▪ Dr LE Nguyen Tuan Thanh ▪ Email: thanhlnt@tlu.edu.vn ▪ Msc LAI Tuan Anh ▪ Email: laituananh@tlu.edu.vn EXAMS AND GRADING ▪ The course will include two multiple choice quarterly, a midterm and a comprehensive final examination ▪ Grading will be based on the following components: Attendance 5% Laboratory exercises 20% Homework (other than lab) 15% Multiple Choice Examinations (2) 20% Midterm Examination 15% Final Examination 25% HOMEWORKS ▪ Assigned weekly on the piazza forum ▪ Students submit homeworks on piazza with a zip files including all necessary files The name of the zip file as well as the title of the email should be: CIVE3066_59NKN_HWK n_Student’s name ▪ where n is the number of the current homework ▪ for example: CIVE3066_59NKN_HWK1_NguyenVanA ▪ Late homework is not accepted ▪ Solutions are posted on piazza or presented in class after due date ▪ Must be your own work Copied work will have the note GENERAL CLASS POLICIES Students are expected to: ▪ Attend regularly ▪ Ask questions ▪ If you not understand what the lecturer is saying or if you detect any errors ▪ Access the course forum piazza regularly ▪ Respect the lecture time ▪ Turn off or silence your cell phones before the start of class ▪ Respect assignment deadlines: late submissions will not be accepted ▪ Be honest: ▪ Violations of the academic integrity policies may include: cheating, plagiarism, aiding academic dishonesty, fabrication, lying, bribery, and threatening behavior COURSE CONTENT EXTENDS: NUMERICAL MODELING & RISK ANALYSIS (CIVE3045) Introduction Exploratory data analysis Fundamental of probability Random variables Fitting distributions Hypothesis testing Decision making for a single sample Building empirical models Simple linear regression RECOMMENDED TEXTBOOKS ▪ Engineering Statistics-Fifth Edition, Montgomery, D.C., G.C Runger and N.F Hubele, John Wiley & Sons, Inc., 2011 ▪ Probability Concepts in Engineering- Second Edition, Ang, A and W Tang, John Wiley & Sons, Inc ▪ Geographic Information Systems and Science, Longley, P., John Wiley & Sons, Inc ▪ Applied Numerical Methods with MATLAB for Engineers and Scientists, Chapra, S.C., McGraw Hill OTHER MATERIALS ▪ MATLAB Statistics Toolbox, MathWorks Inc ▪ MATLAB Curve Fitting Toolbox, MathWorks Inc ▪ Numerical Computing with MATLAB, Moler, C ▪ Think Stats: Exploratory Data Analysis in Python, Allen B Downey, 2014 EXPLORATORY DATA ANALYSIS Engineering Systems and Decision Analysis (CIVE3066) Instructors: Nguyen-Tuan-Thanh LE (thanhlnt@tlu.edu.vn) Based on the CIVE203 - Engineering system and decision analysis - Colorado state University, USA THE CENTRAL LIMIT THEOREM (5) n=20 n=200 n=1000 Impact of sample size Based on the CIVE203 - Engineering system and decision analysis - Colorado state University, https://onlinecourses.science.psu.edu/stat504/node/16484848 22 CONTENTS Statistical inference Point estimation The central limit theorem Confidence intervals Based on the CIVE203 - Engineering system and decision analysis - Colorado state University, https://onlinecourses.science.psu.edu/stat504/node/16484848 23 BASIC CONCEPTS OF CONFIDENCE INTERVALS (1) ▪ Based on the CIVE203 - Engineering system and decision analysis - Colorado state University, https://onlinecourses.science.psu.edu/stat504/node/16484848 24 BASIC CONCEPTS OF CONFIDENCE INTERVALS (2) ▪ α/ Based on the CIVE203 - Engineering system and decision analysis - Colorado state University, https://onlinecourses.science.psu.edu/stat504/node/16484848 1α a α/ b 25 BASIC CONCEPTS OF CONFIDENCE INTERVALS (3) ▪ 1α α a 1α Based on the CIVE203 - Engineering system and decision analysis - Colorado state University, https://onlinecourses.science.psu.edu/stat504/node/16484848 α b 26 CI ON THE POPULATION MEAN – LARGE RANDOM SAMPLES (1) ▪ 27 CI ON THE POPULATION MEAN – LARGE RANDOM SAMPLES: EXAMPLE ▪ 28 CI ON THE POPULATION MEAN – LARGE RANDOM SAMPLES (3) ▪ α a α α Based on the CIVE203 - Engineering system and decision analysis - Colorado state University, https://onlinecourses.science.psu.edu/stat504/node/16484848 α b 29 CI ON THE POPULATION MEAN – SMALL RANDOM SAMPLES (1) ▪ 30 CI ON THE POPULATION MEAN – SMALL RANDOM SAMPLES (2) ▪ 31 CI ON THE POPULATION MEAN – SMALL RANDOM SAMPLES (4) ▪ Based on the CIVE203 - Engineering system and decision analysis - Colorado state University, https://onlinecourses.science.psu.edu/stat504/node/16484848 32 CI ON THE POPULATION MEAN – SMALL RANDOM SAMPLE (4) 33 CI ON THE POPULATION MEAN – SMALL RANDOM SAMPLES (5): REMARKS ▪ 34 CI ON THE POPULATION MEAN – SMALL RANDOM SAMPLES: EXAMPLE ▪ 35 CI ON THE POPULATION MEAN – SMALL RANDOM SAMPLES (6) ▪ Based on the CIVE203 - Engineering system and decision analysis - Colorado state University, https://onlinecourses.science.psu.edu/stat504/node/16484848 36