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國立中山大學 111學年度第1學期 課程教學大綱
National Sun Yat-sen University 111Academic year1st Semester Course syllabus
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中文名稱
Course name(Chinese) |
統計基礎及R語言應用 |
課號
Course Code |
MIS984A |
英文名稱
Course name(English) |
INTRODUCTION TO STATISTICS: WITH APPLICATIONS IN R |
課程類別
Type of the course |
講授類 | 必選修
Required/Selected | 必修 |
系所
Dept./faculty |
資訊管理學系電子商務與商業分析數位學習碩士在職專班 |
授課教師
Instructor |
李捷
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學分
Credit |
3 |
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因應嚴重特殊傳染性肺炎(武漢肺炎)，倘若後續需實施遠距授課，授課方式調整如下： |
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因應嚴重特殊傳染性肺炎(武漢肺炎)，倘若後續需實施遠距授課，評分方式調整如下： |
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課程大綱 Course syllabus |
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課程目標 Objectives |
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授課方式 Teaching methods |
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非同步介紹R語言撰寫，及例題演算。同步遠距進行統計概念和統計方法的解說。另有中文講義和R-code 講義隨課堂提供。
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評分方式﹝評分標準及比例﹞Evaluation (Criteria and ratio)等第制單科成績對照表 letter grading reference
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1.課堂參與：5%
2.作業：25%
3.期中測驗：25%
4.期末報告：10%
5.期末報告-書面：25%
6.讀書報告：10%
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參考書/教科書/閱讀文獻 Reference book/ textbook/ documents
〔請遵守智慧財產權觀念，不可非法影印。教師所提供之教材供學生本人自修學習使用,不得散播及做為商業用途〕
No copies for intellectual property rights. Textbooks provided by the instructor used only for self-study, can not broadcast or commercial use
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以自編講義為主，學生可參考坊間統計課本，但並非必要。
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每週課程內容及預計進度 Weekly scheduled progress |
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| 週次 | 日期 | 授課內容及主題 | | Week | Date | Content and topic | | 1 | 2022/09/04~2022/09/10 | 學生選課 | | 2 | 2022/09/11~2022/09/17 | 課程介紹 | | 3 | 2022/09/18~2022/09/24 | Descriptive Statistics -distributions and measurements | | 4 | 2022/09/25~2022/10/01 | Normality test and equal variance | | 5 | 2022/10/02~2022/10/08 | Hypothesis and Confidence Interval | | 6 | 2022/10/09~2022/10/15 | One sample t- and z-test | | 7 | 2022/10/16~2022/10/22 | Two sample test t- and z-test | | 8 | 2022/10/23~2022/10/29 | Simple Linear Regression: Model Selection and Diagnosis | | 9 | 2022/10/30~2022/11/05 | Midterm exam | | 10 | 2022/11/06~2022/11/12 | Multiple Linear Regression Model Selection and Diagnosis | | 11 | 2022/11/13~2022/11/19 | Multiple Linear Regression Model Selection and Diagnosis | | 12 | 2022/11/20~2022/11/26 | Data Transformation | | 13 | 2022/11/27~2022/12/03 | Logistics Regression: Model Selection and Diagnosis | | 14 | 2022/12/04~2022/12/10 | Logistics Regression: Model Selection and Diagnosis | | 15 | 2022/12/11~2022/12/17 | Non-parametric Analysis | | 16 | 2022/12/18~2022/12/24 | Cluster Analysis | | 17 | 2022/12/25~2022/12/31 | Final presentation | | 18 | 2023/01/01~2023/01/07 | Final project report due |
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課業討論時間 Office hours |
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時段1 Time period 1:
時間 Time：星期二17:00-19:30
地點 Office/Laboratory：office
時段2 Time period 2：
時間 Time：星期四17:00-19:30
地點 Office/Laboratory：office
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系所學生專業能力/全校學生基本素養與核心能力 basic disciplines and core capabilitics of the dcpartment and the university |
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系所學生專業能力/全校學生基本素養與核心能力
basic disciplines and core capabilities of the department and the university | 課堂活動與評量方式
Class activities and evaluation | | 本課程欲培養之能力與素養 This course enables students to achieve. | 紙筆考試或測驗 Test. | 課堂討論︵含個案討論︶ Group discussion (case analysis). | 個人書面報告、作業、作品、實驗 Indivisual paper report/ assignment/ work or experiment. | 群組書面報告、作業、作品、實驗 Group paper report/ assignment/ work or experiment. | 個人口頭報告 Indivisual oral presentation. | 群組口頭報告 Group oral presentation. | 課程規劃之校外參訪及實習 Off-campus visit and intership. | 證照/檢定 License. | 參與課程規劃之校內外活動及競賽 Participate in off-campus/ on-campus activities and competitions.
| 課外閱讀 Outside reading. | | ※系所學生專業能力 Basic disciplines and core capabilities of the department | |
| ※全校學生基本素養與核心能力 Basic disciplines and core capabilities of the university | |
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本課程與SDGs相關項目：The course relates to SDGs items: |
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本課程校外實習資訊: This course is relevant to internship: |
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