Statistics is Easy: Case Studies on Real Scientific Datasets
暫譯: 統計學簡易入門:真實科學數據集案例研究
Singh Katari, Manpreet, Tyagi, Sudarshini, Shasha, Dennis
- 出版商: Morgan & Claypool
- 出版日期: 2021-04-08
- 售價: $1,760
- 貴賓價: 9.5 折 $1,672
- 語言: 英文
- 頁數: 74
- 裝訂: Hardcover - also called cloth, retail trade, or trade
- ISBN: 1636390919
- ISBN-13: 9781636390918
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相關分類:
機率統計學 Probability-and-statistics
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相關主題
商品描述
Computational analysis of natural science experiments often confronts noisy data due to natural variability in environment or measurement. Drawing conclusions in the face of such noise entails a statistical analysis.
Parametric statistical methods assume that the data is a sample from a population that can be characterized by a specific distribution (e.g., a normal distribution). When the assumption is true, parametric approaches can lead to high confidence predictions. However, in many cases particular distribution assumptions do not hold. In that case, assuming a distribution may yield false conclusions.
The companion book Statistics is Easy! gave a (nearly) equation-free introduction to nonparametric (i.e., no distribution assumption) statistical methods. The present book applies data preparation, machine learning, and nonparametric statistics to three quite different life science datasets. We provide the code as applied to each dataset in both R and Python 3. We also include exercises for self-study or classroom use.
商品描述(中文翻譯)
計算分析自然科學實驗時,常常會面臨由於環境或測量的自然變異性所產生的噪音數據。在這種噪音的情況下得出結論需要進行統計分析。
參數統計方法假設數據是來自一個可以用特定分佈(例如,正態分佈)來描述的母體的樣本。當這一假設成立時,參數方法可以導致高置信度的預測。然而,在許多情況下,特定的分佈假設並不成立。在這種情況下,假設一個分佈可能會導致錯誤的結論。
伴隨著的書籍《Statistics is Easy!》提供了一個(幾乎)不需要方程式的非參數(即,無分佈假設)統計方法的介紹。本書將數據準備、機器學習和非參數統計應用於三個截然不同的生命科學數據集。我們提供了在 R 和 Python 3 中應用於每個數據集的代碼。我們還包括了自學或課堂使用的練習題。