However, I did find the inclusion of practice problems at the end of each section vs. all together the end of the whole chapter (which is the new arrangement in the 4th edition) to be a challenge - specifically, this made it difficult for me to identify easily where sections ended, and in some places, to follow the train of thought across sections. While the examples did connect with the diversity within our country or i.e. This book offers an easily accessible and comprehensive guide to the entire market research process, from asking market research questions to collecting and analyzing data by means of quantitative methods. It is a pdf download rather than strictly online so the format is more classical textbook as would be experienced in a print version. The fourth edition is a definite improvement over previous editions, but still not the best choice for our curriculum. The text also provides enough context for students to understand the terminologies and definitions, especially this textbook provides plenty of tips for each concept and that is very helpful for students to understand the materials. I see essentially no errors in this book. The final chapters, "Introduction to regression analysis" and "Multiple and logistical regression" fit nicely at the end of the text book. The book appears professionally copy-edited and easy to read. This may allow the reader to process statistical terminology and procedures prior to learning about regression. It should be appealing to the learners, dealing with a real-life case for better and deeper understanding of Binomial distribution, Normal approximation to the Binomial distribution. I value the unique organization of chapters, the format of the material, and the resources for instructors and students. This is the most innovative and comprehensive statistics learning website I have ever seen. The book uses relevant topics throughout that could be quickly updated. The approach is mathematical with some applications. I find this method serves to give the students confidence in knowing that they understand concepts before moving on to new material. This book does not contain anything culturally insensitive, certainly. In addition to the above item-specific comments: #. For example, types of data, data collection, probability, normal model, confidence intervals and inference for single proportions. The t distribution is introduced much later. However, classical measures of effect such as confidence intervals and R squared appear when appropriate though they are not explicitly identified as measures of effect. I think it would be better to group all of the chapter's exercises until each section can have a greater number of exercises. Many examples use real data sets that are on the larger side for intro stats (hundreds or thousands of observations). Each section within a chapter build on the previous sections making it easy to align content. Also, the convenient sample is covered. Access even-numbered exercise solutions. For example, I can imagine using pieces of Chapters 2 (Probability) and 3 (Distributions of random variables) to motivate methods that I discuss in service courses. The final chapter (8) gives superficial treatments of two huge topics, multiple linear regression and logistic regression, with insufficient detail to guide serious users of these methods. 2017 Generation of Electrical Energy is written primarily for the undergraduate students of electrical engineering while also covering the syllabus of AMIE and act as a OpenIntro Statistics covers a first course in statistics, providing a rigorous introduction to appliedstatistics that is clear, concise, and accessible. Reviewed by Barbara Kraemer, Part-time faculty, De Paul University School of Public Service on 6/20/17, The texts includes basic topics for an introductory course in descriptive and inferential statistics. Examples stay away from cultural topics. Reviewed by Kendall Rosales, Instructor and Service Level Coordinator, Western Oregon University on 8/20/20, There is more than enough material for any introductory statistics course. The modularity is creative and compares well. Similar to most intro The text is easily and readily divisible into subsections. This textbook is widely used at the college level and offers an exceptional and accessible introduction for students from community colleges to the Ivy League. Reviewed by Lily Huang, Adjunct Math Instructor , Bethel University on 11/13/18, The text covers all the core topics of statisticsdata, probability and statistical theories and tools. David M. Diez, Harvard School of Public Health, Christopher D. Barr, Harvard School of Public Health, Reviewed by Hamdy Mahmoud, Collegiate Assistant Professor, Virginia Tech on 5/16/22, This book covers almost all the topics needed for an introductory statistics course from introduction to data to multiple and logistic regression models. The sections on these advanced topics would make this a candidate for more advanced-level courses than the introductory undergraduate one I teach, and I think will help with longevity. Probability is an important topic that is included as a "special topic" in the course. The B&W textbook did not seem to pose any problems for me in terms of distortion, understanding images/charts, etc., in print. The textbook price was updated from $14.99 for the 3rd Edition to $20 for the 4th Edition, which we believe will be a sustainable price point that helps support OpenIntro as it scales into new subjects. It covers all the standard topics fully. This could be either a positive or a negative to individual instructors. Supposedly intended for "introductory statistics courses at the high school through university levels", it's not clear where this text would fit in at my institution. My biggest complaint is that The writing style and context to not treat students like Phd academics (too high of a reading level), nor does it treat them like children (too low of a reading level). Intro Stats - 4th Edition - Solutions and Answers | Quizlet Statistics Intro Stats 4th Edition ISBN: 9780321825278 David E. Bock, Paul Velleman, Richard D. De Veaux Textbook solutions Verified Chapter 1: Stats Start Here Exercise 1 Exercise 2 Exercise 3 Exercise 4 Exercise 5 Exercise 6 Exercise 7 Exercise 8 Exercise 9 Exercise 10 Exercise 11 The section on model selection, covering just backward elimination and forward selection, seems especially old-fashioned. There are also matching videos for students who need a little more help to figure something out. Table. Students can check their answers to the odd questions in the back of the book. Materials in the later sections of the text are snaffled upon content covered in these initial chapters. They authors already discussed 1-sample inference in chapter 4, so the first two sections in chapter 5 are Paired Data and Difference of Means, then they introduce the t-distribution and go back to 1-sample inference for the mean, and then to inference for two means using he t-distribution. For example, it is claimed that the Poisson distribution is suitable only for rare events (p. 148); the unequal-variances form of the standard error of the difference between means is used in conjunction with the t-distribution, with no mention of the need for the Satterthwaite adjustment of the degrees of freedom (p. 231); and the degrees of freedom in the chi-square goodness-of-fit test are not adjusted for the number of estimated parameters (p. 282). Choosing the population proportion rather than the population mean to be covered in the foundation for inference chapter is a good idea because it is easier for students to understand compared to the population mean. The text is accurate due to its rather straight forward approach to presenting material. I found virtually no issues in the grammar or sentence structure of the text. Single proportion, two proportions, goodness of fit, test for independence and small sample hypothesis test for proportions. I do think there are some references that may become obsolete or lost somewhat quickly; however, I think a diligent editorial team could easily update data sets and questions to stay current. Black and white paperback edition. The interface of the book appears to be fine for me, but more attractive colors would make it better. There are also pictures in the book and they appear clear and in the proper place in the chapters. More modern approaches to statistical methods, however, will need to include concepts of important to the current replicability crisis in research: measures of effect, extensive applications of power analyses, and Bayesian alternatives. In addition all of the source code to build the book is available so it can be easily modified. Tables and graphs are sensibly annotated and well organized. The authors make effective use of graphs both to illustrate the For example, a scatterplot involving the poverty rate and federal spending per capita could be updated every year. They have done an excellent job choosing ones that are likely to be of interest to and understandable by students with diverse backgrounds. The content is well-organized. Some examples of this include the discussion of anecdotal evidence, bias in data collection, flaws in thinking using probability and practical significance vs statistical significance. OpenIntro Statistics covers a first course in statistics, providing a rigorous introduction to applied statistics that is clear, concise, and accessible. OpenIntro Statistics Solutions for OpenIntro Statistics 4th David M. Diez Get access to all of the answers and step-by-step video explanations to this book and +1,700 more. The topics are in a reasonable order. Perhaps we don't help the situation much with the way we begin launching statistical terminology while demonstrating a few "concepts" on a white board. I found the book's prose to be very straightforward and clear overall. There is no evidence that the text is culturally insensiteve or offensive. The authors spend many pages on the sampling distribution of mean in chapter 4, but only a few sentences on the sampling distribution of proportion in chapter 6; 2) the authors introduced independence after talking about the conditional probability. Statistics is not a subject that becomes out of date, but in the last couple decades, more emphasis has been given to usage of computer technology and relevant data. This book is quite good and is ethically produced. Some more separation between sections, and between text vs. exercises would be appreciated. David M. Diez, Mine etinkaya-Rundel, Christopher D. Barr . There are lots of graphs in the book and they are very readable. Things flow together so well that the book can be used as is. The supplementary material for this book is excellent, particularly if instructors are familiar with R and Latex. The only visual issues occurs in some graphs, such as on page 40-41, which have maps of the U.S. using color to show intensity. The organization for each chapter is also consistent. This selection of topics and their respective data sets are layered throughout the book. In general I was satisfied. I did not find any grammatical errors or typos. At first when reviewing, I found it to be difficult for to quickly locate definitions and examples and often focus on the material. OpenIntro Statistics supports flexibility in choosing and ordering topics. This textbook is widely used at the college level and offers an exceptional and accessible introduction for students from community colleges to the Ivy League. I was sometimes confused by tables with missing data or, as was the case on page 11, when the table was sideways on the page. Errors are not found as of yet. Especially like homework problems clearly divided by concept. The introduction of jargon is easy streamlined in after this example introduction. Some topics in descriptive statistics are presented without much explanation, such as dotplots and boxplots. The best statistics OER I have seen yet. One-way analysis of variance is introduced as a special topic, with no mention that it is a generalization of the equal-variances t-test to more than two groups. The textbook has been thoroughly vetted with an estimated 20,000 students using it annually. Reviewed by Denise Wilkinson, Professor of Mathematics, Virginia Wesleyan University on 4/20/21, This text book covers most topics that fit well with an introduction statistics course and in a manageable format. The examples and solutions represent the information with formulas and clear process. The topics all proceed in an orderly fashion. The presentation is professional with plenty of good homework sets and relevant data sets and examples. The sections seem easily labeled and would make it easy to skip particular sections, etc. The bookmarks of chapters are easy to locate. Jargon is introduced adequately, though. The revised 2nd edition of this book provides the reader with a solid foundation in probability theory and statistics as applied to the physical sciences, engineering and related fields. The later chapters (chapters 4-8) are built upon the knowledge from the former chapters (chapters 1-3). OpenIntro Statistics textbook solutions from Chegg, view all supported editions. Reviewed by Bo Hu, Assistant Professor, University of Minnesota on 7/15/14, This book covers topics in a traditional curriculum of an introductory statistics course: probabilities, distributions, sampling distribution, hypothesis tests for means and proportions, linear regression, multiple regression and logistic One of the good topics is the random sampling methods, such as simple sample, stratified, I also particularly like that once the basics chapters are covered, the instructor can then pick and choose those topics that will best serve the course or needs of students. There is an up-to-date errata maintained on the website. The document was very legible. 325 and 357). In addition, the book is written with paragraphs that make the text readable. The student-facind end, while not flashy or gamified in any way, is easy to navigate and clear. I did not notice any culturally sensitive examples, and no controversial or offensive examples for the reader are presented. It is clear that the largest audience is assumed to be from the United States as most examples draw from regions in the U.S. The drawbacks of the textbook are: 1) it doesn't offer how to use of any computer software or graphing calculator to perform the calculations and analyses; 2) it didn't offer any real world data analysis examples. The content is accurate in terms of calculations and conclusions and draws on information from many sources, including the U.S. Census Bureau to introduce topics and for homework sets. Jump to Page . Share. The format is consistent throughout the textbook. Professors looking for in-depth coverage of research methods and data collection techniques will have to look elsewhere. read more. In particular, examples and datasets about county characteristics, elections, census data, etc, can become outdated fairly quickly. This is the third edition and benefits from feedback from prior versions. I do like the case studies, videos, and slides. My interest in this text is for a graduate course in applied statistics in the field of public service. 2019, 422 pages. Mine Cetinkaya-Rundel is the Director of Undergraduate Studies and Assistant Professor of the Practice in the Department of Statistical Science at Duke University. The examples will likely become dated, but that is always the case with statistics textbooks; for now, they all seem very current (in one example, we solve for the % of cat videos out of all the videos on Youtube). Fisher's exact test is not even mentioned. 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