當期課號 |
3150 |
Course Number |
3150 |
授課教師 |
張志榮 |
Instructor |
CHANG,JYH RONG |
中文課名 |
統計學 |
Course Name |
Statistics |
開課單位 |
企業管理系(四進)二A |
Department |
|
修習別 |
必修 |
Required/Elective |
Required |
學分數 |
3 |
Credits |
3 |
課程目標 |
本課程旨在使學生熟悉統計基本概念、原理及技巧,使其能對相關資料作組織、彙整、衡量並根據資料所得的結果加以評估及推論以幫助吾人作決策,一學年課程包括1. 統計學的意義與應用 2. 資料的類型 3. 機率的基本概念 4. 敘述統計的種類、計算與應用5.常用的機率分配模型 6. 抽樣分配與其應用 7. 估計的觀念與介紹 8. 假設檢定的介紹與其應用9.卡方檢定 10. 變異數分析 11.相關與簡單線性迴歸分析。 |
Objectives |
The purpose of this course is to acquaint the students with the statistical concepts,fundamentals and techniques needed to organize,measure and evaluate data that may then be used to support people to make better decisions in the face of uncertainty.Topics include:1. The meaning and application of statistics 2. Type of data 3. Basic principle of probability 4. Introduction of descriptive statistics and its applications5.Discrete and continuous probability 6. Sampling distribution and its application 7. Introduction and concept of estimation 8. Hypothesis testing 9.Chi-square testing 10.Analysis of variance 11.Correlation and simple linear regression analysis |
教材 |
教材:統計學 劉明德等著 全華科技圖書 2004年4月 參考書:1.基本統計學 林惠玲 陳正倉合著 雙葉書廊 2004年 2.統計學-觀念.理論與方法 Statistics-Concepts,Theory and Methods 賀力行等著 前程出版 2003年 3.Modern Elementary Statistics, John E Freund, 11th edition, Pearson Education Inc. 2004 |
Teaching Materials |
|
成績評量方式 |
期中考-30% 期末考-40% 上課出席,參與狀況及平時考-30% |
Grading |
Mid-term Exam.-30% Final Exam.-40% Presence.Participation,and Quiz-30% |
教師網頁 |
|
教學內容 |
本課程主要在使學生熟悉統計基本概念.原理及計巧,使其能對相關資料作組織,彙整,衡量並根據資料所得的結果加以評估及推論以幫助吾人作決策.主要內容:1.常用之機率分配2.抽樣與抽樣分配 3.統計估計 4.統計假設檢定 5.卡方檢定 6.相關分析與迴歸分析 |
Syllabus |
The purpose of this course is to acquaint the students with the statistical concepts,fundamentals, and techniques needed to organize, measure,and evaluate data that may then be used to support people to make better decisions in the face of uncertainty. Topics include:1.Probability distribution 2. Sampling and sampling distribution 3. Estimation 4. Tests of hypothesis 5. Chi-square tests 6.Correlation analysis and regression analysis |