課程與核心能力關聯配比(%) |
課程目標之教學方法與評量方法 |
課程目標 |
核心能力 |
配比(%) |
教學方法 |
評量方法 |
The aim of this course is to equip you with the best skill for solving your own statistical problems/projects with C++ and R programming provided that you study hard during the whole semester. |
1.數學專業思維與邏輯推理知識 |
2.數學分析專業知識 |
3.計算科學專業知識 |
5.數學模型建構與軟體應用 |
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授課內容(單元名稱與內容、習作/每週授課、考試進度-共16週加自主學習) |
週次 |
授課內容 |
第1週 |
I will focus on C++ during the 1st week to the 9th week.
Week1: Introduction
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第2週 |
Week2: Data, variables, and calculations |
第3週 |
Week3: Decisions and loops |
第4週 |
Week4 & 5: Functions |
第5週 |
Week4 & 5: Functions |
第6週 |
Week6: Applications: Stochastic models
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第7週 |
Week7: Arrays, strings, and pointers
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第8週 |
Week8: IO and file IO |
第9週 |
Week9: Defining your own data type |
第10週 |
Week10: Introduction to using R |
第11週 |
Week11: Univariate data; Bivariate data; Random data |
第12週 |
Week12:Elementary simulations; R Data Structures; |
第13週 |
Week13: Various methods for generating random variates |
第14週 |
⚠️‼️12月11號(三)晚上6:30~9:00安排期中考(上機考試),本週不上課 |
第15週 |
🗣️期末口頭報告(開始日期將依修課人數調整) |
第16週 |
🗣️期末口頭報告
📚自主學習週(期末書面報告製作與整理)
📚自主學習週(期末書面報告製作與整理) |
自主學習 內容 |
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學習評量方式 |
Miscellanea (including homework, mini projects, quizzes, class presence etc.): 30\% (without a fixed schedule)
Midterm exam ({about the 14th week}): 35\%
Final project (viva voce and written): 35\% |
教科書&參考書目(書名、作者、書局、代理商、說明) |
Simulation, 4th Edition, by Sheldon M. Ross, Academic Press.
C++ programming: Ivor Horton’s Beginning Visual C++ 2013, by Ivor Horton, Wiley
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課程教材(教師個人網址請列在本校內之網址) |
iLearning |
課程輔導時間 |
TBA |
聯合國全球永續發展目標(連結網址) |
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