9781498779982 - Applied Statistical Inference with MINITAB®, Second Edition de Lesik, Sally A. (20 resultados)

hardcover. Condición: New. 2nd Edition. Ships in a BOX from Central Missouri! UPS shipping for most packages, (Priority Mail for AK/HI/APO/PO Boxes).

Hardcover. Condición: Very Good. 2nd Edition. Oversized hardcover, xvii + 478 pages, NOT ex-library. Interior is clean and bright throughout with unmarked text, free of inscriptions and stamps, firmly bound. Boards show gentle shelfworn marks and scratches. Issued without a dust jacket. -- Contents: 1 Introduction [What is Statistics?; What This Book Is About; Summary Tables and Graphical Displays; Descriptive Representations of Data; Inferential Statistics; Populations; Different Ways to Collect Data; Types & Scales of Variables; Types of Analyses; Entering Data into Minitab; Best Practices] 2 Graphs and Charts [Introduction; Frequency Distributions and Histograms; Using Minitab to Create Histograms; Stem-and-Leaf Plots; Using Minitab to Create Stem-and-Leaf Plots; Bar Charts; Using Minitab to Create a Bar Chart; Boxplots; Using Minitab to Create Boxplots; Scatter Plots; Using Minitab to Create Scatter Plots; Marginal Plots; Using Minitab to Create Marginal Plots; Matrix Plots; Using Minitab to Create a Matrix Plot; Best Practices] 3 Descriptive Representations of Data and Random Variables [Descriptive Statistics; Measures of Central Tendency; Measures of Variability; Using Minitab to Calculate Descriptive Statistics; More on Statistical Inference; Discrete Random Variables; Sampling Distributions; Continuous Random Variables; Standard Normal Distribution; Non-Standard Normal Distributions; Other Discrete and Continuous Probability Distributions; Binomial Distribution; Poisson Distribution; t-Distribution; Chi-Square Distribution; F-Distribution; Using MINTIAB to Graph Probability Distributions] 4 Statistical Inference for One Sample [Introduction; Confidence Intervals; Using Minitab to Calculate Confidence Intervals for a Population Mean; Hypothesis Testing: A One-Sample t-Test for a Population Mean; Using Minitab for a One-Sample t-Test; Power Analysis for a One-Sample t-Test; Using Minitab for a Power Analysis for a One-Sample t-Test; Confidence Intervals and Hypothesis Tests for One Proportion; Using Minitab for a One-Sample Proportion; Power Analysis for a One-Sample Proportion; Confidence Intervals and Hypothesis Tests for One-Sample Variance; Confidence Intervals for One-Sample Variance; Hypothesis Tests for One-Sample Variance; Using Minitab for One-Sample Variance; Power Analysis for One-Sample Variance; Confidence Intervals for One-Sample Count Data; Using Minitab to Calculate Confidence Intervals for a One-Sample Count Variable; Hypothesis Test for a One-Sample Sample Count Variable; Using Minitab to Conduct a Hypothesis Test for a One-Sample Count Variable; Using Minitab for a Power Analysis for a One-Sample Poisson; A Note About One- and Two-Tailed Hypothesis Tests] 5 Statistical Inference for Two-Samples [Introduction; Confidence Interval for the Difference between Two Means; Using Minitab to Calculate a Confidence Interval for the Difference between Two Means; Hypothesis Tests for the Difference between Two Means; Using Minitab to Test the Difference between Two Means; Using Minitab to Create an Interval Plot; Using Minitab for a Power Analysis for a Two-Sample t-Test; Paired Confidence Interval and t-Test; Using Minitab for a Paired Confidence Interval and t-Test; Differences Between Two Proportions; Using Minitab for Two-Sample Proportion Confidence Intervals and Hypothesis Tests; Power Analysis for a Two-Sample Proportion; Confidence Intervals and Hypothesis Tests for Two Variances; Using Minitab for Testing Two Sample Variances; Power Analysis for a Two-Sample Variances; Confidence Intervals and Hypothesis Tests for Two Count Variables; Using Minitab for a Two-Sample Poisson; Power Analysis for a -Sample Poisson Rate; Best Practices] 6 Simple Linear Regression 7 More on Simple Linear Regression 8 Multiple Regression Analysis 9 More on Multiple Regression 10 Analysis of Variance (ANOVA) 11 Nonparametric Statistics 12 Two Way Analysis of Variance and Basic Time Series.

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Hardcover. Condición: Brand New. 2nd new edition. 472 pages. 10.50x7.00x1.50 inches. In Stock.

Gebunden. Condición: New. Dieser Artikel ist ein Print on Demand Artikel und wird nach Ihrer Bestellung fuer Sie gedruckt. Sally A. Lesik is a professor of mathematics at Central Connecticut State University. Dr. Lesik has taught many mathematics, statistics, engineering, and physics courses. Her primary research is in applied statistical inference. .

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Hardcover. Condición: Brand New. 2nd new edition. 472 pages. 10.50x7.00x1.50 inches. In Stock. This item is printed on demand.

Buch. Condición: Neu. nach der Bestellung gedruckt Neuware - Printed after ordering - Praise for the first edition:'One of my biggest complaints when I teach introductory statistics classes is that it takes me most of the semester to get to the good stuff-inferential statistics. The author manages to do this very quickly.if one were looking for a book that efficiently covers basic statistical methodology and also introduces statistical software [this text] fits the bill.' -The American StatisticianApplied Statistical Inference with MINITAB, Second Edition distinguishes itself from other introductory statistics textbooks by focusing on the applications of statistics without compromising mathematical rigor. It presents the material in a seamless step-by-step approach so that readers are first introduced to a topic, given the details of the underlying mathematical foundations along with a detailed description of how to interpret the findings, and are shown how to use the statistical software program Minitab to perform the same analysis.Gives readers a solid foundation in how to apply many different statistical methods.MINITAB is fully integrated throughout the text.Includes fully worked out examples so students can easily follow the calculations.Presents many new topics such as one- and two-sample variances, one- and two-sample Poisson rates, and more nonparametric statistics.Features mostly new exercises as well as the addition of Best Practices sections that describe some common pitfalls and provide some practical advice on statistical inference.This book is written to be user-friendly for students and practitioners who are not experts in statistics, but who want to gain a solid understanding of basic statistical inference. This book is oriented towards the practical use of statistics. The examples, discussions, and exercises are based on data and scenarios that are common to students in their everyday lives.