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Data-Science-For-Beginners/translations/th/1-Introduction/04-stats-and-probability/assignment.ipynb

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8.7 KiB

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"## บทนำสู่ความน่าจะเป็นและสถิติ\n",
"## งานที่ได้รับมอบหมาย\n",
"\n",
"ในงานนี้ เราจะใช้ชุดข้อมูลของผู้ป่วยโรคเบาหวานที่นำมาจาก [ที่นี่](https://www4.stat.ncsu.edu/~boos/var.select/diabetes.html)\n"
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"import pandas as pd\n",
"import numpy as np\n",
"\n",
"df = pd.read_csv(\"../../data/diabetes.tsv\",sep='\\t')\n",
"df.head()"
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" AGE SEX BMI BP S1 S2 S3 S4 S5 S6 Y\n",
"0 59 2 32.1 101.0 157 93.2 38.0 4.0 4.8598 87 151\n",
"1 48 1 21.6 87.0 183 103.2 70.0 3.0 3.8918 69 75\n",
"2 72 2 30.5 93.0 156 93.6 41.0 4.0 4.6728 85 141\n",
"3 24 1 25.3 84.0 198 131.4 40.0 5.0 4.8903 89 206\n",
"4 50 1 23.0 101.0 192 125.4 52.0 4.0 4.2905 80 135"
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"ในชุดข้อมูลนี้ คอลัมน์มีดังนี้:\n",
"* Age และ sex อธิบายตัวเองได้ชัดเจน\n",
"* BMI คือดัชนีมวลกาย\n",
"* BP คือความดันโลหิตเฉลี่ย\n",
"* S1 ถึง S6 เป็นการวัดค่าต่าง ๆ ของเลือด\n",
"* Y คือการวัดเชิงคุณภาพของการพัฒนาของโรคในช่วงหนึ่งปี\n",
"\n",
"มาศึกษาชุดข้อมูลนี้โดยใช้วิธีการของความน่าจะเป็นและสถิติ\n",
"\n",
"### งานที่ 1: คำนวณค่าเฉลี่ยและค่าความแปรปรวนสำหรับค่าทั้งหมด\n"
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"### งานที่ 4: ทดสอบความสัมพันธ์ระหว่างตัวแปรต่างๆ กับการพัฒนาของโรค (Y)\n",
"\n",
"> **คำแนะนำ** เมทริกซ์ความสัมพันธ์จะให้ข้อมูลที่มีประโยชน์ที่สุดเกี่ยวกับค่าที่มีความสัมพันธ์กัน\n"
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"\n---\n\n**ข้อจำกัดความรับผิดชอบ**: \nเอกสารนี้ได้รับการแปลโดยใช้บริการแปลภาษา AI [Co-op Translator](https://github.com/Azure/co-op-translator) แม้ว่าเราจะพยายามให้การแปลมีความถูกต้อง แต่โปรดทราบว่าการแปลอัตโนมัติอาจมีข้อผิดพลาดหรือความไม่แม่นยำ เอกสารต้นฉบับในภาษาต้นทางควรถือเป็นแหล่งข้อมูลที่เชื่อถือได้ สำหรับข้อมูลที่สำคัญ ขอแนะนำให้ใช้บริการแปลภาษาจากผู้เชี่ยวชาญ เราไม่รับผิดชอบต่อความเข้าใจผิดหรือการตีความที่ผิดพลาดซึ่งเกิดจากการใช้การแปลนี้\n"
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