# Search Results for "introductory-statistics"

## Introductory Statistics, Student Solutions Manual (e-only)

**Author**: Sheldon M. Ross**Publisher:**Academic Press**ISBN:**0123846692**Category:**Mathematics**Page:**320**View:**3457

Introductory Statistics, Student Solutions Manual (e-only)

## Introductory Statistics with R

**Author**: Peter Dalgaard**Publisher:**Springer Science & Business Media**ISBN:**9780387790534**Category:**Mathematics**Page:**364**View:**2177

This book provides an elementary-level introduction to R, targeting both non-statistician scientists in various fields and students of statistics. The main mode of presentation is via code examples with liberal commenting of the code and the output, from the computational as well as the statistical viewpoint. Brief sections introduce the statistical methods before they are used. A supplementary R package can be downloaded and contains the data sets. All examples are directly runnable and all graphics in the text are generated from the examples. The statistical methodology covered includes statistical standard distributions, one- and two-sample tests with continuous data, regression analysis, one-and two-way analysis of variance, regression analysis, analysis of tabular data, and sample size calculations. In addition, the last four chapters contain introductions to multiple linear regression analysis, linear models in general, logistic regression, and survival analysis.

## Introductory Statistics

**Author**: J. Gosling**Publisher:**Pascal Press**ISBN:**9781864410150**Category:**Mathematical statistics**Page:**342**View:**8182

A comprehensive, self-paced, step-by-step statistics course for tertiary students.

## Introductory Statistics

**Author**: Prem S. Mann**Publisher:**John Wiley & Sons**ISBN:**0470444665**Category:**Mathematics**Page:**744**View:**1648

When it comes to learning statistics, Mann delivers the information that business professionals need. The new edition incorporates the most up-to-date methods and applications to present the latest information in the field. It focuses on explaining how to apply the concepts through case studies and numerous examples. Data integrated throughout the chapters come from a wide range of disciplines and media sources. Over 200 examples are included along with marginal notes and step-by-step solutions. The Decide for Yourself feature also helps business professionals explore real-world problems and solutions.

## Introductory Statistics

*A Conceptual Approach Using R*

**Author**: William B. Ware,John M. Ferron,Barbara Manning Miller**Publisher:**Routledge**ISBN:**0805836519**Category:**EDUCATION**Page:**497**View:**8399

"This comprehensive and uniquely organized text is aimed at undergraduate and graduate level statistics courses in education, psychology, and other social sciences. The focus throughout is more on conceptual understanding, the attainment of statistical literacy and thinking than on learning a set of tools and procedures. An organizational scheme built around common issues and problems rather than statistical techniques allows students to understand the conceptual nature of statistical procedures and to focus more on cases and examples of analysis. Whenever possible, presentations contain explanations of the underlying reasons behind a technique. Importantly, this is one of the first statistics texts in the social sciences using R as the principal statistical package. Key features include the following. Conceptual Focus--The focus throughout is more on conceptual understanding and attainment of statistical literacy and thinking than on learning a set of tools and procedures. Problems and Cases--Chapters and sections open with examples of situations related to the forthcoming issues, and major sections ends with a case study. For example, after the section on describing relationships between variables, there is a worked case that demonstrates the analyses, presents computer output, and leads the student through an interpretation of that output. Continuity of Examples--A master data set containing nearly all of the data used in the book's examples is introduced at the beginning of the text. This ensures continuity in the examples used across the text. Companion Website--A companion website contains instructions on how to use R, SAS, and SPSS to solve the end-of-chapter exercises and offers additional exercises. Field Tested--The manuscript has been field tested for three years at two leading institutions"--

## Introductory Statistics

**Author**: Sheldon M. Ross**Publisher:**Academic Press**ISBN:**012804361X**Category:**Mathematics**Page:**828**View:**3360

Introductory Statistics, Fourth Edition, reviews statistical concepts and techniques in a manner that will teach students not only how and when to utilize the statistical procedures developed, but also how to understand why these procedures should be used. The text's main merits are the clarity of presentation, contemporary examples and applications from diverse areas, an explanation of intuition, and the ideas behind the statistical methods. Concepts are motivated, illustrated, and explained in a way that attempts to increase one's intuition. To quote from the preface, it is only when a student develops a feel or intuition for statistics that she or he is really on the path toward making sense of data. Ross achieves this goal through a coherent mix of mathematical analysis, intuitive discussions, and examples. Applications and examples refer to real-world issues, such as gun control, stock price models, health issues, driving age limits, school admission ages, use of helmets, sports, scientific fraud, and many others. Examples relating to data mining techniques using the number of Google queries or Twitter tweets are also considered. For this fourth edition, new topical coverage includes sections on Pareto distribution and the 80-20 rule, Benford's law, added material on odds and joint distributions and correlation, logistic regression, A-B testing, and more modern (big data) examples and exercises. Includes new section on Pareto distribution and the 80-20 rule, Benford’s law, odds, joint distribution and correlation, logistic regression, A-B testing, and examples from the world of analytics and big data Comprehensive edition that includes the most commonly used statistical software packages (SAS, SPSS, Minitab), ISM, SSM, and an online graphing calculator manual Presents a unique, historical perspective, profiling prominent statisticians and historical events to motivate learning by including interest and context Provides exercises and examples that help guide the student towards indpendent learning using real issues and real data, e.g. stock price models, health issues, gender issues, sports, and scientific fraud

## IBM SPSS for Introductory Statistics

*Use and Interpretation, Fourth Edition*

**Author**: George A. Morgan,Nancy L. Leech,Gene W. Gloeckner,Karen C. Barrett**Publisher:**Taylor & Francis**ISBN:**1136909443**Category:**Education**Page:**243**View:**6397

"Designed to help students analyze and interpret research data using IBM SPSS, this book describes the use of statistics in user-friendly, non-technical language to show readers how to choose the appropriate statistic based on the design, interpret output, and write about the results. The authors prepare readers for all of the steps in the research process, from design and data collection, to writing about the results. Discussions of writing about outputs, data entry and checking, reliability assessment, testing assumptions, and computing descriptive and inferential parametric and nonparametric statistics are included. SPSS syntax, along with the output, is provided for those who prefer this format"--Provided by publisher.

## Introductory Statistics for Biology

**Author**: R. E. Parker,Reginald Ernest Parker**Publisher:**Cambridge University Press**ISBN:**9780521427784**Category:**Mathematics**Page:**132**View:**6792

This introductory text presents the use of statistical methods as an integral part of biological investigation, yet one whose superficial complexities have deterred many biologists from using them. The author argues that the difficulties, such as they are, do not lie in mathematical manipulation, but in grasping a few simple, but unfamiliar concepts. He emphasizes the need for precisely defining problems and for careful selection of the most appropriate methods - a wide range of which are described and illustrated. Each chapter ends with a set of problems which are intended to help the student gain practical experience. No previous knowledge is assumed, and the student is encouraged to develop a competent and critical approach to analysing numerical data. In this second edition, the scope of the book has been extended, problems have been solved in a more satisfactory way, and a greater number of illustrative examples have been added.

## Introductory Statistics

**Author**: Textbook Equity Edition**Publisher:**Lulu.com**ISBN:**130489164X**Category:**Education**Page:**740**View:**3596

Introductory Statistics is designed for the one-semester, introduction to statistics course and is geared toward students majoring in fields other than math or engineering. This text assumes students have been exposed to intermediate algebra, and it focuses on the applications of statistical knowledge rather than the theory behind it. The foundation of this textbook is Collaborative Statistics, by Barbara Illowsky and Susan Dean. Additional topics, examples, and ample opportunities for practice have been added to each chapter. The development choices for this textbook were made with the guidance of many faculty members who are deeply involved in teaching this course. These choices led to innovations in art, terminology, and practical applications, all with a goal of increasing relevance and accessibility for students. We strove to make the discipline meaningful, so that students can draw from it a working knowledge that will enrich their future studies and help them make sense of the world around them.

## Using R for Introductory Statistics

**Author**: John Verzani**Publisher:**CRC Press**ISBN:**0203499891**Category:**Mathematics**Page:**432**View:**803

The cost of statistical computing software has precluded many universities from installing these valuable computational and analytical tools. R, a powerful open-source software package, was created in response to this issue. It has enjoyed explosive growth since its introduction, owing to its coherence, flexibility, and free availability. While it is a valuable tool for students who are first learning statistics, proper introductory materials are needed for its adoption. Using R for Introductory Statistics fills this gap in the literature, making the software accessible to the introductory student. The author presents a self-contained treatment of statistical topics and the intricacies of the R software. The pacing is such that students are able to master data manipulation and exploration before diving into more advanced statistical concepts. The book treats exploratory data analysis with more attention than is typical, includes a chapter on simulation, and provides a unified approach to linear models. This text lays the foundation for further study and development in statistics using R. Appendices cover installation, graphical user interfaces, and teaching with R, as well as information on writing functions and producing graphics. This is an ideal text for integrating the study of statistics with a powerful computational tool.