查詢教學大綱與進度

教學大綱與進度

課程基本資料：

學年期課號課程名稱階段學分時數修教師班級人撤備註

112-2 326740 統計數據分析 1 3.0 3 ★ 朴維鎮工管三甲
工管三乙 15 0 工管三甲乙丙合開

學年期	課號	課程名稱	階段	學分	時數	修	教師	班級	人	撤	備註
112-2	326740	統計數據分析	1	3.0	3	★	朴維鎮	工管三甲工管三乙	15	0	工管三甲乙丙合開

教學大綱與進度：

教師姓名朴維鎮　教師諮商時間(Office Hours)

Email eugenepark993@gmail.com

最後更新時間 2024-05-24 16:29:47

課程大綱 This course is an introduction to statistical computing and will be taught in Python. Python is widely used not only in the engineering but also in natural science, medicine, biology, physics, and business. This course will introduce you to a vibrant and growing community of open source data analysts that is pushing the state of the art in data analysis and presentation. (Another benefit to you as students is that open source software is free!) This course’s main objective is to: learn how to take raw data, explore it, and present the results in a useful way. Thus, in this course, you will learn all of the basic skills needed to do each of these steps with the statistical language Python.

課程進度 Week 1-2 Introduction to ‘Data Analysis and Graphics’ and Python Week 3 Operations in Python Week 4-5 Vector and matrix, tabulation and graphics Week 6-7 Probability distributions Week 8-9 Basic statistics Week 10-11 Hypothesis tests Week 12 ANOVA Week 13-14 Simple linear regression Week 15-16 Multiple linear regressio Week 17 Presentation I Week 18 Presentation II

評量方式與標準 Exam or assignment or presentation: 90 % Attendance: 10 %

使用教材、參考書目或其他 【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
(1) Engineering Statistics (5th Ed., Wiley) by Montgomery, Runger, and Hubele (ISBN: 978-0-324-59433-1) (2) Introduction to Python for Econometrics, Statistics and Data Analysis (4th Ed.) by Kevin Sheppard

課程諮詢管道 Email or i-school system.
Office hour: Thursday 11:00 ~ 12:00

I will notify students of the lecture schedules in periods 17 and 18 weeks through the email and Line. And, more details on 'Linear regression analysis' will be given.

課程對應SDGs指標

課程是否導入AI

備註
Email and MS Teams

I will notify students of the lecture schedules in periods 17 and 18 weeks through the email and Line. And, more details on 'Linear regression analysis' will be given.

教師姓名	朴維鎮　教師諮商時間(Office Hours)
Email	eugenepark993@gmail.com
最後更新時間	2024-05-24 16:29:47
課程大綱	This course is an introduction to statistical computing and will be taught in Python. Python is widely used not only in the engineering but also in natural science, medicine, biology, physics, and business. This course will introduce you to a vibrant and growing community of open source data analysts that is pushing the state of the art in data analysis and presentation. (Another benefit to you as students is that open source software is free!) This course’s main objective is to: learn how to take raw data, explore it, and present the results in a useful way. Thus, in this course, you will learn all of the basic skills needed to do each of these steps with the statistical language Python.
課程進度	Week 1-2 Introduction to ‘Data Analysis and Graphics’ and Python Week 3 Operations in Python Week 4-5 Vector and matrix, tabulation and graphics Week 6-7 Probability distributions Week 8-9 Basic statistics Week 10-11 Hypothesis tests Week 12 ANOVA Week 13-14 Simple linear regression Week 15-16 Multiple linear regressio Week 17 Presentation I Week 18 Presentation II
評量方式與標準	Exam or assignment or presentation: 90 % Attendance: 10 %
使用教材、參考書目或其他	【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 (1) Engineering Statistics (5th Ed., Wiley) by Montgomery, Runger, and Hubele (ISBN: 978-0-324-59433-1) (2) Introduction to Python for Econometrics, Statistics and Data Analysis (4th Ed.) by Kevin Sheppard
課程諮詢管道	Email or i-school system. Office hour: Thursday 11:00 ~ 12:00 I will notify students of the lecture schedules in periods 17 and 18 weeks through the email and Line. And, more details on 'Linear regression analysis' will be given.
課程對應SDGs指標
課程是否導入AI
備註	Email and MS Teams I will notify students of the lecture schedules in periods 17 and 18 weeks through the email and Line. And, more details on 'Linear regression analysis' will be given.