Library of American University of Madaba
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Rivera, Roberto (Associate professor),
Principles of managerial statistics and data science / Roberto Rivera - Hoboken, NJ : John Wiley & Sons, Inc., 2020 - xxiv, 652 p. ; 24 cm.
Includes bibliographical references and index
Statistics suck; so why do I need to learn about it? -- Concepts in statistics -- Data visualization -- Descriptive statistics -- Introduction to probability -- Discrete random variables -- Continuous random variables -- Properties of sample statistics -- Interval estimation for one population parameter -- Hypothesis testing for one population -- Statistical inference to compare parameters from two populations -- Analysis of variance (ANOVA) -- Simple linear regression -- Multiple linear regression -- Inference on association of categorical variables -- Nonparametric testing -- Forecasting
Available to OhioLINK libraries
"This book introduces the topics of Big Data, data analytics and data science and features the use of open source data. Among the statistical topics described in this book are: data visualization, descriptive measures, probability, probability distributions, the concept of mathematical expectation, confidence intervals, and hypothesis testing. Also covered are analysis of variance, simple linear regression, multiple linear regression and diagnostics, extensions to multiple linear regression models, contingency tables, Chi-square tests, non-parametric methods, and time series method. Chapters include multiple examples showing the application of the theoretical aspects presented. In addition, practice problems are designed to ensure that the reader understands the concepts and can apply them using real data. Most data will come from regions throughout the U.S. though some datasets come from Europe and countries around the world. Moreover, open portal data will be the basis for many of the examples and problems, allowing the instructor to adapt the application to local data with which students can identify. An appendix will include solutions to some of these practice problems"--
9781119486411 1119486416 1119486475 9781119486497 1119486491 9781119486428 1119486424 9781119486473
Management--Statistical methods.
Mathematical statistics.
Statistical decision.
Data mining.
Big data.
Electronic books
HD30.215 / .R58 2020
519.5 / R621
Principles of managerial statistics and data science / Roberto Rivera - Hoboken, NJ : John Wiley & Sons, Inc., 2020 - xxiv, 652 p. ; 24 cm.
Includes bibliographical references and index
Statistics suck; so why do I need to learn about it? -- Concepts in statistics -- Data visualization -- Descriptive statistics -- Introduction to probability -- Discrete random variables -- Continuous random variables -- Properties of sample statistics -- Interval estimation for one population parameter -- Hypothesis testing for one population -- Statistical inference to compare parameters from two populations -- Analysis of variance (ANOVA) -- Simple linear regression -- Multiple linear regression -- Inference on association of categorical variables -- Nonparametric testing -- Forecasting
Available to OhioLINK libraries
"This book introduces the topics of Big Data, data analytics and data science and features the use of open source data. Among the statistical topics described in this book are: data visualization, descriptive measures, probability, probability distributions, the concept of mathematical expectation, confidence intervals, and hypothesis testing. Also covered are analysis of variance, simple linear regression, multiple linear regression and diagnostics, extensions to multiple linear regression models, contingency tables, Chi-square tests, non-parametric methods, and time series method. Chapters include multiple examples showing the application of the theoretical aspects presented. In addition, practice problems are designed to ensure that the reader understands the concepts and can apply them using real data. Most data will come from regions throughout the U.S. though some datasets come from Europe and countries around the world. Moreover, open portal data will be the basis for many of the examples and problems, allowing the instructor to adapt the application to local data with which students can identify. An appendix will include solutions to some of these practice problems"--
9781119486411 1119486416 1119486475 9781119486497 1119486491 9781119486428 1119486424 9781119486473
Management--Statistical methods.
Mathematical statistics.
Statistical decision.
Data mining.
Big data.
Electronic books
HD30.215 / .R58 2020
519.5 / R621