Articles liés à Think Stats 2e
Synopsis
If you know how to program, you have the skills to turn data into knowledge, using tools of probability and statistics. This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python.
By working with a single case study throughout this thoroughly revised book, you'll learn the entire process of exploratory data analysis--from collecting data and generating statistics to identifying patterns and testing hypotheses. You'll explore distributions, rules of probability, visualization, and many other tools and concepts.
New chapters on regression, time series analysis, survival analysis, and analytic methods will enrich your discoveries.
- Develop an understanding of probability and statistics by writing and testing code
- Run experiments to test statistical behavior, such as generating samples from several distributions
- Use simulations to understand concepts that are hard to grasp mathematically
- Import data from most sources with Python, rather than rely on data that's cleaned and formatted for statistics tools
- Use statistical inference to answer questions about real-world data
Les informations fournies dans la section « Synopsis » peuvent faire référence à une autre édition de ce titre.
À propos de l?auteur
Allen Downey is an Associate Professor of Computer Science at the Olin College of Engineering. He has taught computer science at Wellesley College, Colby College and U.C. Berkeley. He has a Ph.D. in Computer Science from U.C. Berkeley and Master's and Bachelor's degrees from MIT.
Les informations fournies dans la section « A propos du livre » peuvent faire référence à une autre édition de ce titre.
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Think Stats: Exploratory Data Analysis
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ISBN 13 : 9781491907337
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Think Stats: Exploratory Data Analysis
Edité par
O'Reilly Media (edition 2), 2014
ISBN 10 : 1491907339
ISBN 13 : 9781491907337
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Paperback
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Paperback. Etat : New. If you know how to program, you have the skills to turn data into knowledge, using tools of probability and statistics. This concise introduction shows you how to perform statistical analysis computationally, rather than mathematically, with programs written in Python. By working with a single case study throughout this thoroughly revised book, you'll learn the entire process of exploratory data analysis - from collecting data and generating statistics to identifying patterns and testing hypotheses. You'll explore distributions, rules of probability, visualization, and many other tools and concepts. New chapters on regression, time series analysis, survival analysis, and analytic methods will enrich your discoveries. Develop an understanding of probability and statistics by writing and testing code Run experiments to test statistical behavior, such as generating samples from several distributions Use simulations to understand concepts that are hard to grasp mathematically Import data from most sources with Python, rather than rely on data that's cleaned and formatted for statistics tools Use statistical inference to answer questions about real-world data. N° de réf. du vendeur LU-9781491907337
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