A panorama of statistics : perspectives, puzzles and paradoxes in statistics / by Sowey, Eric, Books24x7, Inc

Table of Contents: “…-- How statistics differs from mathematics -- Statistical literacy- essential in the 21st century -- Statistical inquiry on the web -- Part II Statistical description -- Trustworthy statistics are accurate, meaningful and relevant -- Let's hear it for the standard deviation! -- Index numbers- time travel for averages -- The beguiling ways of bad statistics I -- The beguiling ways of bad statistics II -- Part III Preliminaries to inference -- Puzzles and paradoxes in probability -- Some paradoxes of randomness -- Hidden risks for gamblers -- Models in statistics -- The normal distribution: history, computation and curiosities -- Part IV Statistical inference -- The pillars of applied statistics- estimation -- The pillars of applied statistics- hypothesis testing -- 'Data snooping' and the significance level in multiple testing -- Francis Galton and the birth of regression -- Experimental design- piercing the veil of random variation -- In praise of Bayes -- Part V Some statistical byways -- Quality in statistics -- History of ideas: statistical personalities and the personalities of statisticians -- Statistical eponymy -- Statistical 'laws' -- Statistical artefacts -- Part VI Answers -- Answers to the chapter questions.…”
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U Can : statistics for dummies / by Rumsey, Deborah J. (Deborah Jean), 1961-, Unger, David, 1950-, Safari Books Online

Table of Contents: “…Grabbing Some Basic Statistical JargonData; Data set; Variable; Population; Statistic; Parameter; Mean (Average); Median; Standard deviation; Percentile; Standard score; Distribution and normal distribution; Central Limit Theorem; z-values; Margin of error; Confidence interval; Hypothesis testing; p-values; Statistical significance; Correlation, regression, and two-way tables; Drawing Credible Conclusions; Reeling in overstated results; Questioning claims of cause and effect; Becoming a Sleuth, Not a Skeptic; Part II Number-Crunching Basics; Chapter 4 Crunching Categorical Data.…”
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Learn R for Applied Statistics : With Data Visualizations, Regressions, and Statistics. by Hui, Eric Goh Ming, Safari Books Online

Table of Contents: “…Reading Data Files; Reading a CSV File; Writing a CSV File; Reading an Excel File; Writing an Excel File; Reading an SPSS File; Writing an SPSS File; Reading a JSON File; Basic Data Processing; Selecting Data; Sorting; Filtering; Removing Missing Values; Removing Duplicates; Some Basic Statistics Terms; Types of Data; Mode, Median, Mean; Mode; Median; Mean; Interquartile Range, Variance, Standard Deviation; Range; Interquartile Range; Variance; Standard Deviation; Normal Distribution; Modality; Skewness; Binomial Distribution; The summary() and str() Functions…”
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Machine learning with R : discover how to build machine learning algorithms, prepare data, and dig deep into data prediction techniques with R / by Lantz, Brett, Safari Books Online

Table of Contents: “…Measuring spread -- variance and standard deviationExploring categorical variables; Measuring the central tendency -- the mode; Exploring relationships between variables; Visualizing relationships -- scatterplots; Examining relationships -- two-way cross-tabulations; Summary; Chapter 3: Lazy Learning -- Classification Using Nearest Neighbors; Understanding nearest neighbor classification; The k-NN algorithm; Measuring similarity with distance; Choosing an appropriate k; Preparing data for use with k-NN; Why is the k-NN algorithm lazy?…”
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Robust statistics : theory and methods (with R) / by Maronna, Ricardo A., ProQuest Ebook Subscriptions

Table of Contents: “…Cover; Title Page; Copyright; Contents; Preface; Preface to the First Edition; About the Companion Website; Chapter 1 Introduction; 1.1 Classical and robust approaches to statistics; 1.2 Mean and standard deviation; 1.3 The "three sigma edit" rule; 1.4 Linear regression; 1.4.1 Straight-line regression; 1.4.2 Multiple linear regression; 1.5 Correlation coefficients; 1.6 Other parametric models; 1.7 Problems; Chapter 2 Location and Scale; 2.1 The location model; 2.2 Formalizing departures from normality; 2.3 M-estimators of location; 2.3.1 Generalizing maximum likelihood…”
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Risk Modelling in General Insurance : From Principles to Practice. by Gray, Roger J., PALCI EBSCO books

Table of Contents: “…3.6.2 Asymptotic approximations3.7 Statistics for compound distributions; 3.8 The individual risk model; 3.8.1 The mean and variance for the individual risk model; 3.8.2 The distribution function and moment generating function for the individual risk model; 3.8.3 Approximations for the individual risk model; Exercises; 4: Model based pricing -- setting premiums; 4.1 Premium calculation principles; 4.1.1 The expected value principle (EVP); 4.1.2 The standard deviation principle (SDP); 4.1.3 The variance principle (VP); 4.1.4 The quantile principle (QP); 4.1.5 The zero utility principle (ZUP).…”
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Even you can learn statistics and analytics : an easy to understand guide to statistics and analytics / by Levine, David M., 1946-, Stephan, David, Safari Books Online

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