課程資料

4009 統計學			開課學期：1151		開課班級： 地理系 2
授課教師：雷鴻飛	必修	學期課	學分數：3.0	大義 0407 星期三 09:10-12:00

4009 STATISTICS			2026 Fall		Department of Geography 2
Professor：LEI, HUNG-FEI	Required	Semester	Credits: 3.0	Da Yi 0407 Wednesday 09:10-12:00

發展願景

傳揚中華文化，促進跨領域創新，與時精進，邁向國際
It is our objective to promote Chinese culture, enhance cross-disciplinary innovation, seek constant advancement, and embrace global community.

辦學宗旨

秉承質樸堅毅校訓，承東西之道統，集中外之精華，研究高深學術, 培養專業人才，服務社會，致力中華文化之發揚, 促進國家發展.
Based on our motto—“Temperament, Simplicity, Strength, and Tenacity,” “inheriting the merits of the East and the West” and “absorbing the essence of Chinese and foreign cultures,” we make it our mission to pursue advanced research, develop professional talents, serve the society, promote Chinese culture and support national development.

校教育目標
校基本素養
校核心能力

院教育目標

奠定自然科學與工程基礎，培養持續學習與創新能力。 Establishing a strong foundation in science and engineering, fostering continuous learning and innovation.
強化理論與實務並重，發展多元且跨領域的專業課程。 Providing theoretical and practical training through diverse, interdisciplinary curricula.
推動產學合作與國際交流，提升學生之全球競爭力。 Enhancing global competitiveness through collaboration with academia, industry and international partners.
培育具備系統整合、科技創新與社會責任的專業人才。 Cultivating professionals equipped with system integration, technological innovation, and social responsibility.

院核心能力

自然科學理論與工程知識之整合應用。Integrated application of scientific theories and engineering knowledge.
問題分析、實驗設計與實作驗證之能力。Ability to analyze problems, design experiments, and validate solutions through practical implementation.
邏輯性思考與科技運用之能力。Logical thinking and effective use of technology.
跨領域整合與創新研發。Cross-disciplinary integration and innovative research and development.
國際視野、團隊合作與溝通協調之能力。Global perspectives, teamwork, and effective communication skills.
具備職業倫理與社會責任之專業態度。Professional attitude with a commitment to ethics and social responsibility.

系教育目標

培育理論與實務並重的地理專業人才 To cultivate geography professionals with a well-balanced foundation in both theory and practice.
訓練具卓越的科技專業競爭力人才 To train individuals with outstanding professional and technological competitiveness.
培養具備國際觀及多元化教育人才 To cultivate talents equipped with a global perspective and diverse educational competencies.

系核心能力

具備正確地理專業觀念與認知To possess a sound understanding and conceptual knowledge of geography.
開拓國際視野與跨領域專業技能To develop a global perspective and interdisciplinary professional skills.
問題認知及解決能力To demonstrate the ability to identify problems and formulate effective solutions.
暸解當代科學技術發展To understand developments in contemporary science and technology.
認同地理環境永續發展意識To recognize and value the principles of geographic environmental sustainability.
關懷社會環境的適切性及人與地的和諧共生To demonstrate concern for social and environmental well-being and promote the harmonious coexistence between people and the land.

課程目標

能夠借助統計軟體工具R佐基本統計分析。 To be able to perform basic statistical analysis with the aid of the statistical software tool R.

課程能力

具備正確地理專業觀念與認知To possess a sound understanding and conceptual knowledge of geography. (比重 15%)
開拓國際視野與跨領域專業技能To develop a global perspective and interdisciplinary professional skills. (比重 10%)
問題認知及解決能力To demonstrate the ability to identify problems and formulate effective solutions. (比重 10%)
暸解當代科學技術發展To understand developments in contemporary science and technology. (比重 10%)
認同地理環境永續發展意識To recognize and value the principles of geographic environmental sustainability. (比重 25%)
關懷社會環境的適切性及人與地的和諧共生To demonstrate concern for social and environmental well-being and promote the harmonious coexistence between people and the land. (比重 30%)

課程概述

本課程介紹地理研究常用之古典統計學。授課內容包括統計理論介紹，並使用統計軟體R結合理論進行練習。This course provides you with an introduction to classical statistics, which remains a commonly used tool in Geographical study. Lectures provide an introduction to statistical theory, and practical classes the opportunity to put the theory into practice using the R program.統計學是一門蒐集、組織、並解釋數值事實的科學。隨著在運算與製作圖表之細節上自動化的持續發展，對資料的洞見與統計概念之強調等無法自動化的部分亦日形重要。本課程針對地理學常用之古典統計分析，介紹此部分工具在地理資料之統計分析上的實際應用。授課內容包括古典統計理論介紹，並借助統計軟體工具R，以輔佐統計分析所需之複雜公式的計算。授課內容係依據所採用之教科書，以易於瞭解的方式，扼要地說明統計分析的技術與實用向度。除了統計結果的計算技巧外，同時檢視統計分析的脈絡，教導如何避免在這些工具使用上常見的技術??與誤用。Statistics is the science of collection, organizing, and interpreting numerical facts. As the continuing revolution in computing automates the details of doing calculations and making graphs, an emphasis on statistical concepts and on insight from data becomes both more practical and more important for users who must supply what is not automated. This course provides you with an introduction into using classic statistical analysis in geography with main goal of providing you with a strong foundation in the practical application of statistical analysis with a focus on geographic data. To these ends we will employ R as tools to help calculate the intricate, but straight-forward, formulas needed to conduct statistical analysis. We will rely heavily on the textbook which does a good job of concisely explaining the technical and practical side of statistical analysis in an easy to understand manner. Beyond the technical aspects of calculating statistical results, we will also examine the contextual side of statistical analysis, trying to avoid many of the pitfalls and misuses of these techniques that seem to be so prevalent in many attempted usages of these helpful tools.

授課內容

This course aims to teach students in geography or related fields statistical skills, emphasizing statistical applications, including how to collect, organize, and analyze data to generate actionable insights and evidence-based decisions. Through lectures and exercises, the course explores how statistical concepts can be applied to geographical topics such as urban housing market modeling, climate mapping, biodiversity index analysis, and consumer behavior prediction. Each week includes two interactive lectures introducing statistical methods and one exercise session, using tools such as Excel and R for data analysis and visualization. Students will learn to collect and use publicly available data or the first-hand data from geographical surveys, and to organize and analyze it to complete descriptive statistical interpretations or hypothesis testing with statistical Inference. The course's training objectives are to understand data, formulate critical statistical conclusions, and use and disseminate statistical findings ethically to support the knowledge and decision-making required for issues of spatial location, geographical environment, and landscape ecosystem.

本課旨在教導地理或相關領域學員統計知能，強調統計應用，包括如何搜集、整理、分析數據，使成為可操作的洞見和基於證據的決策。課程中透過講課與練習，探索統計概念如何用於城市住房市場建模、繪製氣候圖、分析生物多樣性指數、預測消費行為等地理學課題。每週課程包括兩堂介紹統計方法的互動式講課，以及一堂統計實習課，使用工具包括Excel以及用於可視化數據的R。藉此學習蒐集、使用公開資料或者第一手地理實察資料，並整理、分析以完成描述統計詮釋或者假說檢定。理解數據背後的運作機制，提出批判性統計結論，以符合倫理的方式來使用、傳播統計發現，以支撐空間區位、地理環境、地景生態所需知能和決策，是本課訓練目的。

授課方式

lectures and exercises

評量方式

課程能力 /評量方式	具備正確地理專業觀念與認知To possess a sound understanding and conceptual knowledge of geography. (比重 15%)	開拓國際視野與跨領域專業技能To develop a global perspective and interdisciplinary professional skills. (比重 10%)	問題認知及解決能力To demonstrate the ability to identify problems and formulate effective solutions. (比重 10%)	暸解當代科學技術發展To understand developments in contemporary science and technology. (比重 10%)	認同地理環境永續發展意識To recognize and value the principles of geographic environmental sustainability. (比重 25%)	關懷社會環境的適切性及人與地的和諧共生To demonstrate concern for social and environmental well-being and promote the harmonious coexistence between people and the land. (比重 30%)
期中測驗評量 Midterm exam25%刪除	20%	20%	20%	20%	10%	10%
期末測驗評量 Final exam25%刪除	20%	20%	20%	20%	10%	10%
出席紀錄考核評量 Attendance25%刪除	20%	20%	20%	20%	10%	10%
實做評量 Class performance25%刪除	20%	20%	20%	20%	10%	10%

上課用書

（師生應遵守智慧財產權及不得非法影印）
Ross, S. M. (2020). Introduction to probability and statistics for engineers and scientists. Academic press.

參考書目

（師生應遵守智慧財產權及不得非法影印）
許皓捷，2025，鳥類公民科學家實戰指南：從田野調查到統計分析與R軟體應用。出版社：許皓捷。

課程需求

要考試

其他需求

輔導時間

• 星期一 11:00-13:00
• 星期三 12:00-14:00
• 星期四 12:00-14:00

教師聯絡資訊

Email：lhf4@ulive.pccu.edu.tw
分機：25532

課程進度

1. 2026/09/16

   Introduction to Data in the Real World

2. 2026/09/23

   Organizing and Visualizing Categorical Data

3. 2026/09/30

   Descriptive Statistics- Measures of Variability

4. 2026/10/07

   Spatial Data Descriptors & Distribution Shapes

5. 2026/10/14

   Probability Foundations and Risk Analysis

6. 2026/10/21

   Continuous Distributions & Gaussian

7. 2026/10/28

   Sampling Distributions & Central Limit Theorem

8. 2026/11/04

   mid-term examination

9. 2026/11/11

   Confidence Intervals for Single Populations

10. 2026/11/18

    Hypothesis Testing Foundations

11. 2026/11/25

    Inference for Single / Two Populations

12. 2026/12/02

    Analysis of Variance (ANOVA)

13. 2026/12/09

    Chi-Square Tests for Categorical Data

14. 2026/12/16

    Correlation & Simple Linear Regression

15. 2026/12/23

    Multiple Regression & Ethical Dissemination- synthesis

16. 2026/12/30

    final examination

17. 2027/01/06

    專題作業

18. 2027/01/13

    專題作業