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The short, teachable chapters and approachable, colloquial style ofIntro Statshas made it the most successful first edition Statistics text. Now a hallmark feature,Intro Statsteaches readers how tothinkstatistically,showproper application of techniques, andtellothers what they have learned. What Can Go Wrong?sections in each chapter give students the tools to detect statistical errors and debunk misuses of statistics, whether intentional or not. Exploring and Understanding Data:Stats Starts Here; Data; Displaying Categorical Data; Displaying Quantitative Data; Describing Distributions Numerically; The Standard Deviation as a Ruler and the Normal Model.Exploring Relationships between Variables:Scatterplots, Association, and Correlation; Linear Regression; Regression Wisdom; Re-Expressing Data: It's easier than you think.Gathering Data:Understanding Randomness; Sample Surveys; Experiments.Randomness and Probability:From Randomness to Probability (LLN); Probability Rules!; Random Variables; Probability Models (Binomial).From the Data at Hand to the World at Large:Sampling Distribution Models (CLT); Confidence Intervals for Proportions; Testing Hypotheses about Proportions; More About Tests; Comparing Two Proportions.Learning About the World:Inferences About Means; Comparing Means; Paired Samples and Blocks.Inference when Variables are Related:Comparing Counts (Chi Square); Inferences for Regression; Analysis of Variance; Multiple Regression. For all readers interested in introductory statistics
statistiek --- Mathematical statistics --- Probability theory --- wiskundige statistiek --- regressie-analyse --- waarschijnlijkheidsleer
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Provides less mathematically minded students with a gentle introduction to basic mathematics and some more advanced topics. Covering algebra, trigonometry, calculus and statistics, it manages to combine clarity of presentation with liveliness of style and sympathy for students' needs. It is straightforward, pragmatic and packed full of illustrative examples, exercises and self-test questions. The essentials of formal mathematics are lucidly explained, with terms such as 'integral' or 'differential equation' fully clarified.Provides a gentle introduction to basic mathematics and
Mathematics. --- Math --- Science --- Mathematics --- wiskunde --- wiskundige statistiek --- 512 --- 512 Algebra --- Algebra
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Linear models (Statistics) --- regressie-analyse --- wiskundige statistiek --- Models, Linear (Statistics) --- Mathematical statistics --- Mathematical models --- Statistics
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Time-series analysis --- tijdreeksanalyse --- wiskundige statistiek --- Analysis of time series --- Autocorrelation (Statistics) --- Harmonic analysis --- Mathematical statistics --- Probabilities
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519.2 --- wiskundige statistiek --- regressie-analyse --- waarschijnlijkheidsleer --- forecasting --- bedrijven, management --- Probability. Mathematical statistics --- 519.2 Probability. Mathematical statistics
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regressie-analyse --- wiskundige statistiek --- Social sciences --- Statistics. --- Statistical methods. --- Statistics --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics
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Statistics --- regressie-analyse --- statistiek --- waarschijnlijkheidsleer --- wiskundige statistiek --- Statistical analysis --- Statistical data --- Statistical methods --- Statistical science --- Mathematics --- Econometrics
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This book explains how computer software is designed to perform the tasks required for sophisticated statistical analysis. For statisticians, it examines the nitty-gritty computational problems behind statistical methods; for mathematicians and computer scientists, it looks at the application of mathematical tools to statistical problems. The first half of the book provides a basic background in numerical analysis emphasizing issues important to statisticians. The next several chapters cover a broad array of statistical tools, such as maximum likelihood and nonlinear regression. The author also treats application of numerical tools: numerical integration and random number generation are explained in a unified manner reflecting complementary views of Monte Carlo methods. The book concludes with an examination of sorting, FFT and the application of other 'fast' algorithms to statistics. Each chapter contains exercises that range from the simple to research problems, as well as examples of the methods at work. Most of the examples are accompanied by demonstration code available on a floppy disk included with the book.
Mathematical statistics --- Numerical analysis. --- 303.0 --- lineaire programmering --- markov-processen --- regressie-analyse --- wiskundige statistiek --- Mathematical analysis --- Data processing. --- Statistische technieken in econometrie. Wiskundige statistiek (algemene werken en handboeken). --- Numerical analysis --- Data processing --- Statistische technieken in econometrie. Wiskundige statistiek (algemene werken en handboeken)
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