Think Stats Probability and Statistics for Programmers Allen Downey
Material type:
TextSeries: Open textbook libraryDistributor: Open Textbook Library Publisher: Green Tea Press Description: 1 online resourceISBN: 9781491907337Subject(s): Computer Science -- TextbooksLOC classification: QA76Online resources: Access online version | Item type | Current library | Call number | URL | Status | Date due | Barcode | Item holds |
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eBook
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Online Access | QA76 (Browse shelf(Opens below)) | Link to resource | Available |
Preface -- 1 Exploratory data analysis -- 2 Distributions -- 3 Probability mass functions -- 4 Cumulative distribution functions -- 5 Modeling distributions -- 6 Probability density functions -- 7 Relationships between variables -- 8 Estimation -- 9 Hypothesis testing -- 10 Linear least squares -- 11 Regression -- 12 Time series analysis -- 13 Survival analysis -- 14 Analytic methods
Think Stats is an introduction to Probability and Statistics for Python programmers. Think Stats emphasizes simple techniques you can use to explore real data sets and answer interesting questions. The book presents a case study using data from the National Institutes of Health. Readers are encouraged to work on a project with real datasets. If you have basic skills in Python, you can use them to learn concepts in probability and statistics. Think Stats is based on a Python library for probability distributions (PMFs and CDFs). Many of the exercises use short programs to run experiments and help readers develop understanding.
Attribution-NonCommercial
In English.
Description based on online resource
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