| 當期課號 |
7371 |
Course Number |
7371 |
| 授課教師 |
林佳靜 |
Instructor |
Lin,Chia Ching |
| 中文課名 |
進階社會統計 |
Course Name |
Advanced Social Statistics |
| 開課單位 |
社會工作系碩士班一A |
Department |
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| 修習別 |
必修 |
Required/Elective |
Required |
| 學分數 |
3 |
Credits |
3 |
| 課程目標 |
本課程涵蓋推論統計的基本原理，及行為科學研究的實際應用，藉由循序結構的教材講義，配合例題的講解實作，使學生能：1.了解統計推論的原理與基本概念；2.就不同性質的資料與研究設計，選擇適當的統計方法；3.依據樣本結果，對母群體作合理的推論；4.正確地解釋研究結果的意義；5.運用統計套裝軟體進行資料分析；6.培養處理資料時應具備的邏輯思考能力，奠定研究社會科學的基礎。 |
Objectives |
This course is designed to cover basic principles of inferential statistics and practical application for the research of behavioral science. Through the highly-organized teaching materials, along with the example explanations and practice, students are able to: 1.understand principles and basic concepts of statistical inference, 2.choose appropriate statistical methods for different data and research designs, 3.make reasonable inference about the population according to the sample result, 4.explain the meaning of research results correctly, 5. analyze data |
| 教材 |
1.Moore (2009). Introduction to the Practice of Statistics(6th Edition), Freeman.
2.Howell, David C. (2002). Statistical methods for psychology (5th Edition). Belmont, CA: Duxbury.
3.王保進(2006) 視窗版SPSS 與行為科學研究(第三版)。台北:心理出版社。 |
Teaching Materials |
1.Moore (2009). Introduction to the Practice of Statistics(6th Edition), Freeman.
2.Howell, David C. (2002). Statistical methods for psychology (5th Edition). Belmont, CA: Duxbury.
3.王保進(2006) 視窗版SPSS 與行為科學研究(第三版)。台北:心理出版社。 |
| 成績評量方式 |
期末考（30％）
作業（含文獻評析）（40％）
課程討論與參與（30％） |
Grading |
Final exam(30%)
Homework（including critical reviews）(40%)
Participation in class(30%) |
| 教師網頁 |
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| 教學內容 |
本課程授課著重在進皆社會統計學之理論與實務分析，讓研究生學習分析統計報表，加強對資料的解釋與分析，課程著重在：1.抽樣方法，2.假設檢定，3.迴歸分析，4.卡方檢定，5.基礎實驗設計學，6.相關分析，7.變異數分析，8.無母數統計等課程內容。 |
Syllabus |
Advanced social statistics is the science of collecting, organizing and interpreting numerical data. The following principles have informed the design of this course:
1.sampling and methods. 2.hypothesis testing, 3.regression, 4.Chi-Square test for categorical data, 5.simple design of experiments, 6.correlation analysis, 7.ANOVA. 8.nonparametric methods. |