課程大綱

課程資訊

課程名稱

統計學下
Statistics (2)

開課學期

107-2

授課對象

生物資源暨農學院農業經濟學系

授課教師

劉鋼

課號

AGEC2002

課程識別碼

607 20012

班次

學分

3.0

全/半年

全年

必/選修

必帶

上課時間

星期三5(12:20~13:10)星期五2,3,4(9:10~12:10)

上課地點

農經大講堂

備註

每週三第5節為實習課，在博雅409上課
總人數上限：60人

Ceiba 課程網頁

http://ceiba.ntu.edu.tw/1072AGEC2002_

課程簡介影片

核心能力關聯

核心能力與課程規劃關聯圖

課程大綱

為確保您我的權利,請尊重智慧財產權及不得非法影印

課程概述

This course covers basic statistical methods such as collecting, describing, summarizing and making inferences of large data sets. It also covers the basic laws of probability needed for making proper inference from data. These theories and methods comprise the fundamental ideas behind much of market research and are heavily used in economics, finance, and management science.

課程目標

The purpose of this course is to provide students with enough understanding of statistical ideas and methodologies to enable them to communicate knowledgeably and effectively in the field of social sciences such as agricultural economics.

課程要求

will be added later...

預期每週課後學習時數

Office Hours

每週一 11:00~12:00 備註： you can see me before or after class if you have questions. You may also contact me via e-mail, or call me in my office. We can also schedule an appointment if necessary.

指定閱讀

 Heumann, Christian, Michael Schomaker, and Shalabh (2016), Introduction to Statistics and Data Analysis, Springer International Publishing Switzerland, ISBN 978-3-319-46162-5 (eBook).
 Verzani, John (2005), Using R for Introductory Statistics, Chapman & Hall, ISBN 0-203-49989-1 Master e-book ISBN (eBook).

參考書目

 Dalgaard, Peter (2008), Introductory Statistics with R, 2nd ed., Springer International Publishing Switzerland, e-ISBN: 978-0-387-79054-1 (eBook).
 林惠玲、陳正倉合著（2013），《統計學–方法與應用》，四版，雙葉書廊有限公司，ISBN 978-986-6672-47-7 （上冊）ISBN 978-986-6672-49-1（下冊）。
 蔡佳泓著（2015），《基礎統計分析–R程式在社會科學之應用》，雙葉書廊有限公司，ISBN 978-986-5668-10-5。
 鄭中平、許清芳著（2015），《R在行為科學之應用》，雙葉書廊有限公司，ISBN 978-986-5668-23-5。

評量方式
(僅供參考)

No.	項目	百分比	說明
1.	Projects	30%	R Projects allow you to practice statistics concepts from lectures by analyzing datasets using R. Some critical techniques in R will be covered during the laboratory sections taught by a graduate teaching associate. R Projects can be done individually or by self-selected groups of two or three people. You need not do each project with the same person. Unless the instructor has granted permission for late submission, grades on late projects will be reduced as follows: 1 or 2 days late -1 point 3 or 4 days late -2 points more than 4 days late – the project received a grade of zero points All Projects are to be typed double space. One-half point will be deducted for multiple or occasional spelling errors. Also, one-half point will be deducted for any assignment submitted with unstapled pages.
2.	Quizzes	20%	Ten quizzes will be given this semester. Each quiz covers basically one chapter and is worth 2 points. No make-up quiz is provided unless the instructor has granted permission. The quizzes are open-book and open-notes.
3.	Final Examination	25%	Note: No make-up exams are given without notes from your doctor or other documents indicating circumstances beyond your control that caused you to miss the official exam dates.
4.	Midterm II	15%	Note: No make-up exams are given without notes from your doctor or other documents indicating circumstances beyond your control that caused you to miss the official exam dates.
5.	Midterm I	10%	Note: No make-up exams are given without notes from your doctor or other documents indicating circumstances beyond your control that caused you to miss the official exam dates.

課程進度

週次	日期	單元主題
第1週	02/22	授課大綱；複習課本1-7章。
第2週	02/27; 03/01	Review R Sampling Distribution
第3週	03/06; 03/08	Sampling Distribution; Estimation
第4週	03/13; 03/15	Estimation
第5週	03/20; 03/22	Estimation
第7週	04/03; 04/05	Spring Break!
第8週	04/10; 04/12	Hypothesis Testing
第9週	04/17; 04/19	Hypothesis Testing
第10週	04/24; 04/26	Goodness-of-fit Test
第11週	05/01; 05/03	ANOVA; Regression
第12週	05/08; 05/10	Regression
第13週	05/15; 05/17	Regression; Midterm A
第14週	05/22; 05/24	Regression; Project 4
第15週	05/29; 05/31	Regression
第16週	06/05; 06/07	Regression; Holiday
第17週	06/12; 06/14	Regression; Project 5
第18週	06/19; 06/21	Final Exam (comprehensive)