國立中山大學 110學年度第1學期 課程教學大綱

National Sun Yat-sen University 110Academic year1st Semester Course syllabus

中文名稱
Course name(Chinese)

應用統計與資料分析

課號
Course Code

HRM674

英文名稱
Course name(English)

APPLIED STATISTICS AND DATA ANALYSIS

課程類別
Type of the course

講授類

必選修
Required/Selected

選修

系所
Dept./faculty

人力資源管理研究所碩士班

授課教師
Instructor

李澄賢    

學分
Credit

3

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:Since COVID-19, if distance learning is necessary, the teaching methods would adjust as follows:

         同步遠距【透過網路直播技術,同時進行線上教學,得採Microsoft Teams、Adobe connect等軟體進行】
同步遠距含錄影【透過網路直播技術,同時進行線上教學並同時錄影,課程內容可擇日再重播,得採Microsoft Teams、Adobe connect等軟體進行】
非同步遠距【課堂錄影或錄製數位教材放置網路供學生可非同時進行線上學習,得採EverCam、PPT簡報錄影、錄音方式進行】
實作類課程,經評估無法採遠距課程教學,後續復課後密集補課

★遠距教學軟體操作說明連結

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:Since COVID-19, if distance learning is necessary, the evaluation would adjust as follows:

        
1.課堂參與與討論 Participation10%
2.作業 Assignments40%
3.個案討論 Case Discussion10%
4.小考 Quizzes15%
5.期末考 Final Exam25%

課程大綱 Course syllabus

         本課程教學大綱已提供完整英文資訊(本選項僅供統計使用,未提供完整英文資訊者,得免勾記)【Provide information of course syllabus in English.(This is for statistical use only. For those who do not provide information of course syllabus in English, do not check this field.)】

本課程主要介紹類別與連續型變項的資料分析與統計推論。學生透過課程會學習以量化與圖表的方式描述資料、選擇與計算統計估計值、執行假設檢定考驗、使用電腦統計軟體進行參數與模型的估計、解釋資料分析的結果,並能與其師長或同儕溝通與討論資料分析的結果。本課程的主題包括: 描述統計、機率與抽樣分配、統計推論、假設檢定、相關與回歸分析。
This course will introduce students to data analysis and statistical inference for both continuous and categorical data. Students will learn to describe data (quantitatively and graphically), to select and compute statistical estimates and conduct hypothesis tests, to use computer packages performing parameter or model estimation, to interpret and report the results of data analysis, and to communicate statistical ideas and results with their colleagues in the business disciplines. General topics covered in class include: Descriptive Statistics, Probability & Sampling Distributions, Statistical Inference, Hypothesis Testing, Correlation, and Regression.



課程目標 Objectives

         1. 熟悉基礎統計知識,例如: 標準誤與信賴區間。
2. 熟悉類別與連續型變項的推論統計。
3. 熟悉一般線性模式與其應用。
4. 能夠使用參數估計或假設檢定進行統計推論,並以有意義的方式詮釋分析結果。
5. 能夠在一般線性模式下,使用參數估計或假設檢定得到分析結果。
6. 能夠以統計分析軟體SPSS進行不同模型的資料分析。
1. Be acquainted with basic statistical concepts, such as standard errors, confidence intervals
2. Be familiar with inferential statistics for both continuous and categorical data
3. Be familiar with the general linear model applications
4. Be able to use the estimation and hypothesis testing procedures, and present a substantive interpretation of the analytic results
5. Be able to estimate and test hypotheses about the parameters in general linear models
6. Be able to set up and execute the statistical software program SPSS to perform data analysis using different analytical techniques





授課方式 Teaching methods

         講授與討論
Lecture & Discussion
備註:第一週9/23(四)上課方式採線上觀看課程介紹錄影與線上資料填寫,已選課同學會收到email, 信件中會有課程預錄youtube連結與google表單。







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

        
1.課堂參與與討論 Participation10%
2.作業 Assignments40%
3.個案討論 Case Discussion10%
4.小考 Quizzes15%
5.期末考 Final Exam25%

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

         教科書
邱皓政、林碧芳 (2017)。統計學:原理與應用(第三版)。臺北:五南出版。
推薦閱讀書單
1. 俞洪亮、蔡義清、莊懿妃 (2012)。商管研究資料分析:SPSS的應用(第二版)。臺北:華泰出版。
2. 楊世瑩(2016) 。SPSS統計分析實務(第二版)。臺北:旗標出版。
3. Jaggia, S., & Kelly, A. (2016). Business Statistics (2nd edition). New York, NY: McGraw-Hill. (臺北:華泰文化代理)
4. Doane, D. P., & Seward, L. E. (2016). Applied Statistics in Business and Economics (5th edition). New York, NY: McGraw-Hill. (臺北:華泰文化代理)




每週課程內容及預計進度 Weekly scheduled progress

        
週次日期授課內容及主題
WeekDateContent and topic
12021/09/19~2021/09/25課程簡介 Course Overview
22021/09/26~2021/10/02描述統計 Descriptive Statistics
32021/10/03~2021/10/09SPSS簡介 Introduction to SPSS
42021/10/10~2021/10/16機率I Probability I
52021/10/17~2021/10/23機率II Probability II
62021/10/24~2021/10/30抽樣分配與信賴區間 Sampling Distributions & Confidence Intervals
72021/10/31~2021/11/06假設檢定 Hypothesis Testing
82021/11/07~2021/11/13推論母體平均數 Inference for Population Mean(s)
92021/11/14~2021/11/20期中考週 Midterm Week
102021/11/21~2021/11/27變異數分析 Analysis of Variances
112021/11/28~2021/12/04類別資料: 推論母體百分比例 Categorical Data: Inference for Population Proportion(s)
122021/12/05~2021/12/11類別資料: 卡方檢定 Categorical Data: Chi-square Tests
132021/12/12~2021/12/18相關 Correlation
142021/12/19~2021/12/25簡單線性回歸I Simple Linear Regression I
152021/12/26~2022/01/01簡單線性回歸II Simple Linear Regression II
162022/01/02~2022/01/08課程內容回顧與複習 Review
172022/01/09~2022/01/15期末考試 Final Exam
182022/01/16~2022/01/22課外閱讀報告

課業討論時間 Office hours

         時段1 Time period 1:
時間 Time:星期二13:00~15:00
地點 Office/Laboratory:CM4081
時段2 Time period 2:
時間 Time:星期三10:00~12:00
地點 Office/Laboratory:CM4081

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

        
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
1.學生能注意倫理的議題及專業倫理。 1. Students are able to pay attention to ethical subjects and professional ethics.            
2.學生能有效溝通並有良好的團隊合作。 2. Students are able to communicate effectively and have good teamwork.V V V V    
3.學生能具備國際觀。 3. Students are able to possess a global perspective.            
4.學生能具備充分的專業知能。 4. Students are able to develop logical thinking and problem solving abilities.VVV V V   V
5.學生能發展邏輯思考及資訊科技能力以解決問題。 5. Students are able to possess appropriate abilities in information technology. VVV V V   V
6.學生能注意並參與社會責任的議題。 6. Students are able to possess sufficient professional competency.            
※全校學生基本素養與核心能力 Basic disciplines and core capabilities of the university
1.表達與溝通能力。 1. Articulation and communication skillsV V V V    
2.探究與批判思考能力。 2. Inquisitive and critical thinking abilitiesVVV V V   V
3.終身學習能力。 3. Lifelong learning           
4.倫理與社會責任。 4. Ethnics and social responsibility           
5.美感品味。 5. Aesthetic appreciation           
6.創造力。 6. Creativity           
7.全球視野。 7. Global perspective           
8.合作與領導能力。 8. Team work and leadershipV V V V    
9.山海胸襟與自然情懷。 9. Broad-mindedness and the embrace of nature            

本課程與SDGs相關項目:The course relates to SDGs items:

        
SDG1-消除貧窮(No Poverty)
SDG2-消除飢餓 (Zero Hunger)
SDG3-良好健康與福祉(Good Health and Well-being)
SDG4-教育品質(Quality Education)
SDG5-性別平等(Gender Equality)
SDG6-乾淨水源與公共衛生(Clean Water and Sanitation)
SDG7-可負擔乾淨能源(Affordable and Clean Energy)
SDG8-優質工作與經濟成長(Decent Work and Economic Growth)
SDG9-工業、創新和基礎建設(Industry,Innovation and Infrastructure)
SDG10-減少不平等(Reduced Inequalities)
SDG11-永續城市(Sustainable Cities and Communities)
SDG12-責任消費與生產(Responsible Consumption and Production)
SDG13-氣候行動(Climate Action)
SDG14-海洋生態(Life Below Water)
SDG15-陸域生態(Life on Land)
SDG16-和平、正義和穩健的制度(Peace,Justice And Strong Institutions)
SDG17-促進目標實現的全球夥伴關係(Partnership for the Goals)
本課程和SDGS無關

本課程校外實習資訊: This course is relevant to internship:

         本課程無註記包含校外實習

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