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課程名稱 |
統計學暨實習
Statistics with Recitation |
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開課學期 |
108-1 |
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授課對象 |
經濟學系 |
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授課教師 |
陳旭昇 |
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課號 |
ECON2022 |
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課程識別碼 |
303 20050 |
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班次 |
01 |
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學分 |
4.0 |
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全/半年 |
半年 |
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必/選修 |
必修 |
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上課時間 |
星期二6,7(13:20~15:10)星期三3,4,5(10:20~13:10) |
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上課地點 |
社科403社科403 |
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備註 |
二67為實習課（含電腦實習）。期初考佔學期總成績10%（考試內容：請參見課程大綱）。
限社會科學院學生(含輔系、雙修生)
總人數上限：80人 |
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Ceiba 課程網頁 |
http://ceiba.ntu.edu.tw/1081ECON2022_01 |
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課程簡介影片 |
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核心能力關聯 |
核心能力與課程規劃關聯圖 |
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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 |
Statistics and Introductory Econometrics are courses that are designed to give you the basic tools to analyze data using statistical method. Statistics focuses on probability model and statistical inference with applications to economic and business problems. Next semester in Introductory Econometrics, Professor Ming-Ching Luoh will teach Econometrics.
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課程目標 |
Statistics and Introductory Econometrics are courses that are designed to give you the basic tools to analyze data using statistical method. Statistics focuses on probability model and statistical inference with applications to economic and business problems. Next semester in Introductory Econometrics, Professor Ming-Ching Luoh will teach Econometrics.
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課程要求 |
9/10 課程介紹
9/11 期初考
期初考內容:
(1) 基礎微積分 (基本函數與極限, 單變量與多變量微分, 單變量與多變量積分, 函數逼近)
(2) 基礎集合論與機率概念 (參見 http://homepage.ntu.edu.tw/~sschen/Probability.pdf)
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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 |
機率與統計推論: R 語言的應用 (第 1 版), 陳旭昇著, 東華書局 (2019 年 1 月出版) |
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參考書目 |
Morris H. DeGroot and Mark J. Schervish (2012), Probability and Statistics (Pearson, 4th Edition) |
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評量方式
(僅供參考) |
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週次 |
日期 |
單元主題 |
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第2週 |
9/17,9/18 |
(1) Random Variables
(2) Multivariate Random Variables |
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第6週 |
10/15,10/16 |
The Normal Distribution and its Applications |
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第8週 |
10/29,10/30 |
(1) Random Samples, Statistics and Sampling Distributions (revised 2019/11/12)
(2) GARBAGE IN, GOSPEL OUT |
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第12週 |
11/26,11/27 |
(1) MLE vs. MME
(2) Interval Estimation
(3) Bootstrap Confidence Intervals (revised 12/10/2019) |
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第14週 |
12/10,12/11 |
Hypothesis Testing |
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第16週 |
12/24,12/25 |
Bootstrap Tests |
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第17週 |
12/31,1/01 |
(1) Other Useful Distributions
(2) Book recommendations |
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第1-1週 |
9/10 |
9/10 課程介紹與機率模型複習
(1) Introduction
(2) Review of Probability Model
Grade Breakdown
Preliminary Exam (September 11, 2019) 10%
1st Midterm Exam (October 23, 2019): 20%
2nd Midterm Exam (December 4, 2019):20%
Final Exam (January 8, 2020):25%
Quizzes (October 2 and November 13, 2018):10%
Homework Assignments: 15%
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第1-2週 |
09/11 |
9/11 期初考
期初考內容:
(1) 基礎微積分 (基本函數與極限, 單變量與多變量微分, 單變量與多變量積分, 函數逼近)
(2) 基礎集合論與機率概念 (參見附檔) |
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第3-2週 |
9/25 |
Lab (Introduction to R, Random Variables, Distributions and pseudo random number generator in R) + TA session
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第4-1週 |
10/01 |
Moments |
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第4-2週 |
10/02 |
Quiz |
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第5-2週 |
10/09 |
Lab (Data, Descriptive Statistics and Graph) + TA session
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第7-1週 |
10/22 |
TA midterm review session
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第7-2週 |
10/23 |
1st Midterm Exam
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第9-1週 |
11/05 |
Asymptotic Theory |
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第9-2週 |
11/06 |
Lab (R Programming, Loops, Monte Carlo Simulation) + TA session
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第10-2週 |
11/13 |
Quiz |
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第11-1週 |
11/19 |
Point Estimation |
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第11-2週 |
11/20 |
Lab (Numerical Maximization and Maximum Likelihood Estimation) + TA session
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第13-1週 |
12/03 |
TA midterm review session
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第13-2週 |
12/04 |
2nd Midterm Exam
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第15-2週 |
12/18 |
Lab (Resampling and Bootstrapping) + TA session
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第18-1週 |
2019/1/07 |
TA final review session
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第18-2週 |
2019/1/8 |
Final Exam
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