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

Statistics is a discipline used for the collection, analysis, interpretation, and inference of data. In the non-computer age, statistics was considered a stepping stone to success, where information is power.
After entering the era of big data, data collection is mostly undertaken by computers, and statistics are used more to avoid wrong data collection and collect valid data instead of generating tens of thousands of data.
Invalid data is used for AI model learning.
This course hopes that through the study of narrative statistics and inferential statistics, it is hoped that future students can effectively guide the direction of AI learning through data types and matrix estimation.
Some courses will be paired 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 inference is an important tool when dealing with certain problems involving random structures.
Major topics include estimation and hypothesis testing. This course introduces students to 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 Translated by Mi Shaogang, Canghai Book Company