Hypothesis Testing假設檢驗講義(中英文版)(ppt 34頁)

Hypothesis Testing假設檢驗講義(中英文版)目錄：
一、解釋由全部數據或抽樣數據所作出決策的不同
二、解釋根據抽樣資料所作出決策的風險
三、說明假設是什麼
四、說明假設檢驗對程序優化的重要性
五、介定 “原假設”和“備擇假設”
六、比較假設檢驗和法庭式決策
七、說明術語“a 風險” 和 “b 風險”
八、說明什麼是 “p數值”

Hypothesis Testing假設檢驗講義(中英文版)內容提要：
Point Estimates of parameters and Confidence Interval Interpretation are both means for making inferences about sample data.
Hypothesis tests are designed to help us make an inference about the true population value at the desired level of confidence.
We will use confidence intervals and tests of sample means, variances and sample standard deviation to investigate difference and cause/ effect relationships using data.
對參數特征值估計和可信區間的詮釋都是得出樣本數據推論的路徑.
假設檢驗是用以幫助我們在需要的可信度上對真實的總體數值進行推論的。
我們將用可信區間和樣本均值、樣本差異及樣本標準偏差測驗來研究使用數據的差別和因果關係。
Hypothesis Tests help determine if an apparent difference is real or could be due to chance. By using data and hypothesis testing, we can quantify our level of confidence that the difference is real.
假設檢驗有助於判斷一個明顯的差別是否真實存在還是偶然的，而且還可以提高差異真實性的可信度.

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