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課程名稱 |
統計學一上
Statistics (I)(1) |
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開課學期 |
111-1 |
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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。
限本系所學生(含輔系、雙修生)
總人數上限：70人 |
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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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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 Keller (12th Edition) |
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參考書目 |
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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. |
Homework |
15% |
Students should complete their homework using Python (Version 3) and Jupyter Lab. They should submit their files (exported as HTML) 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 to a given question. Sharing your answers with other students is strictly prohibited. |
2. |
Project (Dec. 14) |
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. Each group should conduct a 12-minute presentation and turn in your slides, codes, and datasets to NTUCOOL within 24 hours after your presentation. |
3. |
Mid-term Exam (Oct. 26) |
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. |
4. |
Final Exam (Dec. 21) |
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. |
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針對學生困難提供學生調整方式 |
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上課形式 |
以錄影輔助 |
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作業繳交方式 |
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考試形式 |
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其他 |
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週次 |
日期 |
單元主題 |
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第1週 |
2022/09/07 |
Introduction to the class and Python / JupyterLab Notebook
Chapter 1: What is Statistics?
Chapter 2: Graphical Descriptive Techniques I |
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第2週 |
2022/09/14 |
Chapter 3: Graphical Descriptive Techniques II |
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第3週 |
2022/09/21 |
Chapter 4: Numerical Descriptive Techniques |
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第4週 |
2022/09/28 |
Teacher’s Day (One day off) |
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第5週 |
2022/10/05 |
Chapter 6: Probability |
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第6週 |
2022/10/12 |
Chapter 7: Random Variables and Discrete Probability Distributions |
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第7週 |
2022/10/19 |
Chapter 8: Continuous Probability Distributions |
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第8週 |
2022/10/26 |
Mid-term exam in Computer Room |
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第9週 |
2022/11/02 |
Chapter 5: Data Collection and Sampling |
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第10週 |
2022/11/09 |
Chapter 9: Sampling Distributions |
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第11週 |
2022/11/16 |
Chapter 10: Introduction to Estimation |
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第12週 |
2022/11/23 |
Chapter 11: Introduction to Hypothesis Testing |
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第13週 |
2022/11/30 |
Chapter 12: Inference about a Population |
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第14週 |
2022/12/07 |
Chapter 12: Inference about a Population (Continued) |
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第15週 |
2022/12/14 |
Project Presentation |
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第16週 |
2022/12/21 |
Final Exam in Computer Room |
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