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課程名稱 |
統計學一上
Statistics (I)(1) |
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開課學期 |
109-1 |
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授課對象 |
資訊管理學系 |
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授課教師 |
陳靜枝 |
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課號 |
MGT2001 |
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課程識別碼 |
700 20111 |
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班次 |
09 |
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學分 |
3.0 |
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全/半年 |
全年 |
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必/選修 |
必帶 |
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上課時間 |
星期三7,8,9(14:20~17:20) |
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上課地點 |
管二305 |
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備註 |
本課程中文授課,使用英文教科書。週三6實習在管院大電腦教室。與盧信銘合授
限本系所學生(含輔系、雙修生)
總人數上限：70人 |
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Ceiba 課程網頁 |
http://ceiba.ntu.edu.tw/1091MGT2001_09 |
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課程簡介影片 |
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核心能力關聯 |
本課程尚未建立核心能力關連 |
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課程大綱
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為確保您我的權利,請尊重智慧財產權及不得非法影印
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課程概述 |
Solving statistical problems begins with a problem and data. The ability to select the right method by problem objective and data type is a valuable tool for business. This class emphasizes applications and fundamental concepts of statistics as well as provides a practical orientation that teaches students how to identify the correct method, calculate the statistics, and properly interpret the results in the context of the question or decision at hand. Since business decisions are driven by data, students will leave this course equipped with the tools they need to make effective, informed decisions in all areas of the business world. |
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課程目標 |
The students will learn not only the algorithms and techniques used to solve related problems, but also the real-world applications that adopt these methods. The students are encouraged to utilize computers in every respect of this class. Computer software is available for this class. |
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課程要求 |
Students should complete their homework using Python (Version 3) and Jupyter Lab. They should submit their files (*.ipynb) to NTUCOOL. The submission should contain code and results. Homework assignments are due the following week before the class begins (i.e. 2:20 pm). Plagiarism will be harshly punished. Students are allowed to discuss homework questions with each other. The discussion, however, should be about a specific concept or detail instead of the complete answers for a given question. Sharing your answers with other students is strictly prohibited.
Form each group with 5-8 persons. Select a research question that allows you to tell a story using the techniques you learned in this course. Your group should conduct a 12-minute presentation and turn in your slides, codes, and datasets to NTUCOOL within 24 hours after your presentation.
Both mid-term and final exams will be in-class, three-hour, and open-book. Each student will be provided a PC in the exams. No NB is allowed. No discussion is allowed in exams. Cheating will result in severe penalty. |
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預期每週課後學習時數 |
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Office Hours |
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指定閱讀 |
Statistics for Management and Economics by Gerald Keller (11th Edition) |
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參考書目 |
Managerial Statistics by Keller (Taiwan Edition) |
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評量方式
(僅供參考) |
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No. |
項目 |
百分比 |
說明 |
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1. |
Final Exam (Jan. 13) |
35% |
Final exam will be in-class, three-hour, and open-book. Each student will be provided a PC in the exams. No NB is allowed. No discussion is allowed in exams. Cheating will result in severe penalty. |
2. |
Mid-term Exam (Nov. 11) |
35% |
Mid-term Exam will be in-class, three-hour, and open-book. Each student will be provided a PC in the exams. No NB is allowed. No discussion is allowed in exams. Cheating will result in severe penalty. |
3. |
Project Presentation (Jan. 6) |
15% |
Form each group with 5-8 persons. Select a research question that allows you to tell a story using the techniques you learned in this course. Your group should conduct a 12-minute presentation and turn in your slides, codes, and datasets to NTUCOOL within 24 hours after your presentation. |
4. |
Homework |
15% |
Students should complete their homework using Python (Version 3) and Jupyter Lab. They should submit their files (*.ipynb) to NTUCOOL. The submission should contain code and results. Homework assignments are due the following week before the class begins (i.e. 2:20 pm). Plagiarism will be harshly punished. Students are allowed to discuss homework questions with each other. The discussion, however, should be about a specific concept or detail instead of the complete answers for a given question. Sharing your answers with other students is strictly prohibited. |
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週次 |
日期 |
單元主題 |
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第1週 |
2020/09/16 |
Introduction to Python and JupyterLab Notebook |
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第2週 |
2020/09/23 |
Chapter 1: What is Statistics?
Chapter 2: Graphical Descriptive Techniques I |
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第3週 |
2020/09/30 |
Chapter 3: Graphical Descriptive Techniques II |
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第4週 |
2020/10/07 |
Chapter 4: Numerical Descriptive Techniques |
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第5週 |
2020/10/14 |
Chapter 4: Numerical Descriptive Techniques (Continued) |
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第6週 |
2020/10/21 |
Chapter 6: Probability |
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第7週 |
2020/10/28 |
Chapter 7: Random Variables and Discrete Probability Distributions |
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第8週 |
2020/11/04 |
Chapter 8: Continuous Probability Distributions |
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第9週 |
2020/11/11 |
Mid-term exam in Computer Room |
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第10週 |
2020/11/18 |
Chapter 5: Data Collection and Sampling |
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第11週 |
2020/11/25 |
Chapter 9: Sampling Distributions |
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第12週 |
2020/12/02 |
Chapter 10: Introduction to Estimation |
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第13週 |
2020/12/09 |
Chapter 10: Introduction to Estimation (Continued)
Chapter 11: Introduction to Hypothesis Testing |
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第14週 |
2020/12/16 |
Chapter 11: Introduction to Hypothesis Testing (Continued) |
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第15週 |
2020/12/23 |
Chapter 12: Inference about a Population |
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第16週 |
2020/12/30 |
Chapter 12: Inference about a Population (Continued) |
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第17週 |
2021/01/06 |
Project Presentation |
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第18週 |
2021/01/13 |
Final Exam in Computer Room |
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