校際選修

115-1 選課時程

進行中

  • 初選第一階段 6/15/2026
  • 初選第二階段 6/22/2026
  • 校際選修 8/24/2026
  • 初選第三階段 8/31/2026
  • 開學後加退選 9/7/2026
  • 逾期加退選 9/21/2026
選課資源

統計學

Statistics

學期
110-1
學分
3 學分
當期課號
1299
永久課號
DCP1268
開課單位
資訊工程學系
授課教師
紀虹名
校區
光復
類別
選修
上課時間表
週一
週二
1
08:00–08:50
統計學
ED305
2 節連堂
2
09:00–09:50
8
16:30–17:20
統計學
ED305

* 根據陽明交大上課時間表所列

概述

1. 統計在資料分析扮演重要的角色,瞭解統計概念與應用,以推估有效的樣本數,與資料分析前,選擇適當的統計方法,透過此方式處理應用工程與其它領域的資料,產生跨領域合作的機會。 (Statistics plays an important role in data analysis. Understanding statistical concepts and applications can estimate the effective sample sizes. Before data analysis, the appropriate statistical method is choosing. In this way, the data from applied engineering and other fields can be handled. Moreover, opportunities for cross-field cooperation are created.) 2. 課程搭配R語言進行實作練習,作為瞭解數學的思考邏輯,以及熟悉統計的應用。 (This course is paired with R language for practical exercises, which helps to understand the thinking logic of mathematics and to be familiar with the statistical applications.) 3. 課程介紹不同領域研究之實驗設計與數據分析,培養學生瞭解收集數據從無到有的過程,包含觀察、規劃、推估、假設、分析、整理。 (This course also introduces experimental design and data analysis in different fields. Students learn the process of collecting data, including observing, planning, estimating, hypothesizing, analyzing, and organizing.) 4. 開學後第一周和第二週為了防疫,這門課可能會採用線上,有關最新資訊,請參閱新的 E3 或透過信箱聯繫老師。 (This course could be online owing to pandemic prevention in the first and second week after school begins. For the most updated information, please refer to the new E3 or contact teacher via email.

先修科目

None

教學方式

TBD

評分方式

1學期作業 Two homework using R language Final project 2.考試狀況 Two quizzes Midterm and final examinations 3.評量方法 Two homework using R language, each 5 % Final project, 15 % Two quizzes, each 10% Midterm examination, 25 % Final examination, 30 %

課程大綱
  • Introduction to Statistics and R Language
  • Bivariate and Multivariate Distributions and Probability
  • Obtaining Data
  • Quality and Reliability
  • Estimation and Statistical Intervals
  • Testing Statistical Hypotheses
  • The Analysis of Variance
  • Inferential Methods in Regression and Correlation
  • Nonparametric methods
  • Experimental Design
週次計畫
週次主題
第 1 週Data and Distributions, Numerical Summary Measures, Introduction of R Language
第 2 週Bivariate and Multivariate Data and Distributions, Probability and Sampling Distributions
第 3 週Obtaining Data
第 4 週Quality and Reliability
第 5 週Quality and Reliability
第 6 週Estimation and Statistical Intervals
第 7 週Estimation and Statistical Intervals
第 8 週Midterm exam
第 9 週Testing Statistical Hypotheses
第 10 週Testing Statistical Hypotheses
第 11 週The Analysis of Variance
第 12 週The Analysis of Variance
第 13 週Inferential Methods in Regression and Correlation
第 14 週Inferential Methods in Regression and Correlation
第 15 週Nonparametric methods
第 16 週Experimental Design
第 17 週Final exam
第 18 週Final project
教科書

1. J. L. Devore, N. R. Farnum, J. A. Doi, Applied Statistics for Engineers and Scientists, Third Edition, Cengage Learning, 2014. 2. P. Dalgaard, Introductory Statistics with R, Second Edition. Springer Science+Business Media, 2008.

Office Hours
地點
TBD
時間
TBD
聯絡方式
TBD