統計學是一門用於資料收集、分析、說明以及推論的學科。在非電腦時代，統計被認為是尋找成功的踏腳石，即資訊即是力量。
進入大數據時代後，資料的收集多由電腦承擔，統計學更多被利用於避免錯誤的資料收集，收集有效的資料而非產生上萬筆
無效數據供AI模型學習。
本課程希望透過敘述性統計以及推論統計的學習，希望未來學生能透過資料種類以及母體推估有效引導AI學習方向
部分課程將搭配 python/matlab/excel範例

Statistical Technique is a subject used to collect, analyze, explain and recommend data. In the non-computer era, it is considered to be the treading stone for success, and information is strength.
After entering the era of large data, data collection is mostly carried by computers, and statistics is more used to avoid errors in data collection, collecting effective data rather than generating tens of thousands of papers.
Invalid data for AI model learning.
This course hopes to learn from descriptive statistics and recommended statistics. In this course, students will be able to effectively guide AI learning directions through data types and mother estimation.
Some courses will be matched with python/matlab/excel examples

統計推論在處理某些涉及隨機結構的問題時 , 為一種重要的工具。
主要的議題包括估算和假設檢定。本課程引導同學接觸一些相關理論和應用的例子。

Statistical recommendations are an important tool when dealing with certain problems involving random structures.
The main topics include estimation and hypothesis confirmation. This course introduces students to contact some relevant theories and application examples.

1. 機率與統計(Essentials of Probability & Statistics for engineers & scientists) 謬紹綱譯, 滄海書局

1. Essentials of Probability & Statistics for engineers & scientists