Probability & Statistics
Probability & statistics centers on the mathematical study of uncertainty, chance, and data analysis—essential for quantifying variability and making informed predictions. This category covers foundational principles including probability theory, distributions, statistical inference, and hypothesis testing, often underpinning work in science, engineering, economics, and the social sciences.
To focus your reading or research, explore subtopics such as Bayesian analysis for updating beliefs, regression analysis to understand relationships between variables, or stochastic processes and time series for modeling random phenomena across time. These distinct areas help tailor your learning to specialized applications or theoretical interests within the wider field of mathematics.
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Chances Are . . .: Adventures in Probability
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Interrupted Time Series Analysis
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Statistics for the Utterly Confused, 2nd Edition
Statistical Methods in Longitudinal Research: Principles and Structuring Change
Probability, Statistics, and Random Processes for Electrical Engineering
Optimal Sports Math, Statistics, and Fantasy
Analysis for Time-To-Event Data Under Censoring and Truncation
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Data Analysis: A Gentle Introduction for Future Data Scientists
A New Concept for Tuning Design Weights in Survey Sampling: Jackknifing in Theory and Practice
Theory of Rank Tests
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The Upside of Irrationality: The Unexpected Benefits of Defying Logic
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John E. Freund's Mathematical Statistics with Applications (Classic Version)
Applied Statistics for Engineers and Scientists: Using Microsoft Excel & Minitab [With CDROM]
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The Signal and the Noise: Why So Many Predictions Fail--But Some Don't
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Probability 1
Introduction to Mathematical Statistics
Hybrid Censoring Know-How: Designs and Implementations
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