A Modern Introduction to Probability and Statistics

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Bol Probability and statistics are subjects fundamental to data analysis, which, in turn, is essential for efficient artificial intelligence. Probability and statistics are subjects fundamental to data analysis, making them essential for efficient artificial intelligence. Although the foundational concepts of probability and statistics remain constant, what needs to be taught is constantly evolving. The first half of the book introduces probability, conditional probability and the standard probability distributions in the traditional way. The second half considers the power of the modern computer and our reliance on technology to do the calculations for us. Offering a fresh presentation that builds on the author's previous book, Understanding Statistics, this book includes exercises (with solutions at the rear of the book) and worked examples. Chapters close with a brief mention of the relevant R commands and summary of the content. Increasingly difficult mathematical sections are clearly indicated, and these can be omitted without affecting the understanding of the remaining material. Aimed at first year graduates, this book is also suitable for readers familiar with mathematical notation.

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Probability and statistics are subjects fundamental to data analysis, which, in turn, is essential for efficient artificial intelligence. Probability and statistics are subjects fundamental to data analysis, making them essential for efficient artificial intelligence. Although the foundational concepts of probability and statistics remain constant, what needs to be taught is constantly evolving. The first half of the book introduces probability, conditional probability and the standard probability distributions in the traditional way. The second half considers the power of the modern computer and our reliance on technology to do the calculations for us. Offering a fresh presentation that builds on the author's previous book, Understanding Statistics, this book includes exercises (with solutions at the rear of the book) and worked examples. Chapters close with a brief mention of the relevant R commands and summary of the content. Increasingly difficult mathematical sections are clearly indicated, and these can be omitted without affecting the understanding of the remaining material. Aimed at first year graduates, this book is also suitable for readers familiar with mathematical notation.

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Pages: 384, Paperback, Oxford University Press


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Merk Oxford University Press, USA
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  • 9780198943136
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