Table. The later chapters on inferences and regression (chapters 4-8) are built upon the former chapters (chapters 1-3). An interesting note is that they introduce inference with proportions before inference with means. Reviewed by Elizabeth Ward, Assistant Professor , James Madison University on 3/11/19, Covers all of the topics usually found in introductory statistics as well as some extra topics (notably: log transforming data, randomization tests, power calculation, multiple regression, logistic regression, and map data). Some examples in the text are traditional ones that are overused, i.e., throwing dice and drawing cards to teach probability. However, it would not suffice for our two-quarter statistics sequence that includes nonparametrics. Chapters 4-6 on statistical inference are especially strong, and the discussion of outliers and leverage in the regression chapters should prove useful to students who work with small n data sets. These blend well with the Exercises that contain the odd solutions at the end of the text. The final chapters, "Introduction to regression analysis" and "Multiple and logistical regression" fit nicely at the end of the text book. The introduction of jargon is easy streamlined in after this example introduction. The key will be ensuring that the latest research trends/improvements/refinements are added to the book and that omitted materials are added into subsequent editions. The presentation is professional with plenty of good homework sets and relevant data sets and examples. The flow of a chapter is especially good when the authors continue to use a certain example in developing related concepts. 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). Our inaugural effort is OpenIntro Statistics. As well, the authors define probability but this is not connected as directly as it could be to the 3 fundamental axioms that comprise the mathematical definition of probability. The authors use the Z distribution to work through much of the 1-sample inference. This is a particular use of the text, and my students would benefit from and be interested in more social-political-economic examples. I think that these features make the book well-suited to self-study. The language seems to be free of bias. Labs are available in many modern software: R, Stata, SAS, and others. It does a more thorough job than most books of covering ideas about data, study design, summarizing data and displaying data. Journalism, Media Studies & Communications. The graphs are readable in black and white also. None of the examples seemed alarming or offensive. I did not find any grammatical errors or typos. There are no proofs that might appeal to the more mathematically inclined. HS Statistics (2nd Ed) exercise solutions Available to Verified Teachers, click here to apply for access Intro Stat w/Rand & Sim exercise solutions Available to Verified Teachers, click here to apply for access Previous Editions Click below to explore the history of each textbook that is in its 2nd or later edition. Since this particular textbook relies heavily on the use of scenarios or case study type examples to introduce/teach concepts, the need to update this information on occasion is real. Overall it was not offensive to me, but I am a college-educated white guy. Introductory statistics courses prepare students to think statistically but cover relatively few statistical methods. I was concerned that it also might add to the difficulty of analyzing tables. Teachers looking for a text that they can use to introduce students to probability and basic statistics should find this text helpful. OpenIntro Statistics supports flexibility in choosing and ordering topics. The basic theory is well covered and motivated by diverse examples from different fields. This text provides decent coverage of probability, inference, descriptive statistics, bivariate statistics, as well as introductory coverage of the bivariate and multiple linear regression model and logistics regression. The index is decent, but there is no glossary of terms or summary of formula, which is disappointing. 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. read more. There are sections that can be added and removed at the instructors discretion. This is important since examples used authentic situations to connect to the readers. For the most part I liked the flow of the book, though there were a few instances where I would have liked to see some different organization. But, when you understand the strengthsand weaknesses of these tools, you can use them to learn about the world. The topics are not covered in great depth; however, as an introductory text, it is appropriate. The odd-numbered exercises also have answers in the book. This open book is licensed under a Creative Commons License (CC BY-SA). For faculty, everything is very easy to find on the OpenIntro website. We don't have content for this book yet. Also, for how the authors seem to be focusing on practicalities, I was somewhat surprised about some of the organization of the inference sections. Mine Cetinkaya-Rundel is the Director of Undergraduate Studies and Assistant Professor of the Practice in the Department of Statistical Science at Duke University. Overall, I liked the book. I suspect these will prove quite helpful to students. 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. This text book covers most topics that fit well with an introduction statistics course and in a manageable format. The text, though dense, is easy to read. My biggest complaint is that one-sided tests are basically ignored. There is one section that is under-developed (general concepts about continuous probability distributions), but aside from this, I think the book provides a good coverage of topics appropriate for an introductory statistics course. These concepts are reinforced by authentic examples that allow students to connect to the material and see how it is applied in the real world. This is a free textbook for a one-semester, undergraduate statistics course. The distinction and common ground between standard deviation and standard error needs to be clarified. The fourth edition is a definite improvement over previous editions, but still not the best choice for our curriculum. I feel that the greatest strength of this text is its clarity. of Contents 1. For example, types of data, data collection, probability, normal model, confidence intervals and inference for It should be pointed out that logistic regression is using a logistic function to model a binary dependent variable. Reviewed by Leanne Merrill, Assistant Professor, Western Oregon University on 6/14/21, This book has both the standard selection of topics from an introductory statistics course along with several in-depth case studies and some extended topics. Students can check their answers to the odd questions in the back of the book. The examples and exercises seem to be USA-centric (though I did spot one or two UK-based examples), but I do not think that it was being insensitive to any group. I viewed the text as a PDF and was pleasantly surprised at the clarity the fluid navigation that is not the norm with many PDFs. In the PDF of the book, these references are links that take you to the appropriate section. In particular, I like that the probability chapter (which comes early in the text) is not necessary for the chapters on inference. Each chapter consists of 5-10 sections. It would be nice to have an e-book version (though maybe I missed how to access this on the website). This keeps all inference for proportions close and concise helping the reader stay uninterrupted in the topic. My only complaint in this is that, unlike a number of "standard" introductory statistics textbooks I have seen, is that the exercises are organized in a page-wide format, instead of, say, in two columns. This selection of topics and their respective data sets are layered throughout the book. 0% 0% found this document useful, Mark this document as useful. It covers all the standard topics fully. #. 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. Students can easily get confused and think the p-value is in favor of the alternative hypothesis. These updates would serve to ensure the connection between the learner and the material that is conducive to learning. The book is written as though one will use tables to calculate, but there is an online supplement for TI-83 and TI-84 calculator. Calculations by hand are not realistic. Some of these will continue to be useful over time, but others may be may have a shorter shelf life. There are lots of great exercises at the end of each chapter that professors can use to reinforce the concepts and calculations appearing in the chapter. There are many additional resources available for this book including lecture slides, a free online homework system, labs, sample exams, sample syllabuses, and objectives. Chapter 2 covers the knowledge of probabilities including the definition of probability, Law of Large Numbers, probability rules, conditional probability and independence and linear combinations of random variables. One topic I was surprised to see trimmed and placed online as extra content were the calculations for variance estimates in ANOVA, but these are of course available as supplements for the book. It is easy to skip some topics with no lack of consistency or confusion. openintro statistics fourth edition open textbook library . read more. OpenIntro Statistics 4th Edition by David Diez, Christopher Barr, Mine etinkaya-Rundel: 250: Join Chegg Study and get: Guided textbook solutions created by . Save Save Solutions to Openintro Statistics For Later. The rationale for assigning topics in Section 1 and 2 is not clear. The book has relevant and easily understood scientific questions. The chapter summaries are easy to follow and the order of the chapters begin with "Introduction to Data," which includes treatment There are a variety of interesting topics in the exercises that include research on the relationship between honesty, age and self control with children; an experiment on a treatment for asthma patients; smoking habits in the U.K.; a study on migraines and acupuncture; and a study on sinusitis and antibiotics. If you are looking for deep mathematical comprehensiveness of exercises, this may not be the right book, but for most introductory statistics students who are not pursuing deeper options in math/stat, this is very comprehensive. According to the authors, the text is to help students forming a foundation of statistical thinking and methods, unfortunately, some basic topics are missed for reaching the goal. The content that this book focuses on is relatively stable and so changes would be few and far between. The first chapter addresses treatments, control groups, data tables and experiments. This could make it easier for students or instructors alike to identify practice on particular concepts, but it may make it more difficult for students to grasp the larger picture from the text alone. Also, as fewer people do manual computations, interpretation of computer software output becomes increasingly important. Display of graphs and figures is good, as is the use of color. 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. Books; Study; Career; Life; . The book does build from a good foundation in univariate statistics and graphical presentation to hypothesis testing and linear regression. Tables and graphs are sensibly annotated and well organized. Jargon is introduced adequately, though. The nicely designed website (https://www.openintro.org) contains abundant resources which are very valuable for both students and teachers, including the labs, videos, forums and extras. read more. This text provides decent coverage of probability, inference, descriptive statistics, bivariate statistics, as well as introductory coverage of the bivariate and multiple linear regression model and logistics regression. No display issues with the devices that I have. The text is organized into sections, and the numbering system within each chapter facilitates assigning sections of a chapter. Statistics is an applied field with a wide range of practical applications. You dont have to be a math guru to learn from real, interesting data. Data are messy, and statistical tools are imperfect. Also, non-parametric alternatives would be nice, especially Monte Carlo/bootstrapping methods. The title of Chapter 5, "Inference for numerical data", took me by surprise, after the extensive use of numerical data in the discussion of inference in Chapter 4. The text is easily reorganized and re-sequenced. My interest in this text is for a graduate course in applied statistics in the field of public service. Introduction In particular, the malaria case study and stokes case study add depth and real-world meaning to the topics covered, and there is a thorough coverage of distributions. The authors present material from lots of different contexts and use multiple examples. OpenIntro Statistics offers a traditional introduction to statistics at the college level. Christopher D. Barr is an Assistant Research Professor with the Texas Institute for Measurement, Evaluation, and Statistics at the University of Houston. Reviewed by Monte Cheney, Associate Professor of Mathematics, Central Oregon Community College on 8/21/16, More depth in graphs: histograms especially. The definitions and procedures are clear and presented in a framework that is easy to follow. There are a lot of topics covered. The later chapters (chapter 4-8) are self-contained and can be re-ordered. To many texts that cover basic theory are organized as theorem/proof/example which impedes understanding of the beginner. It's very fitting for my use with teachers whose primary focus is on data analysis rather than post-graduate research. The text would not be found to be culturally insensitive in any way, as a large part of the investigations and questions are introspective of cultures and opinions. Overall, I would consider this a decent text for a one-quarter or one-semester introductory statistics textbook. Use of the t-distribution is motivated as a way to "resolve the problem of a poorly estimated standard error", when really it is a way to properly characterize the distribution of a test statistic having a sample-based standard error in the denominator. Each section ends with a problem set. I found the book to be very comprehensive for an undergraduate introduction to statistics - I would likely skip several of the more advanced sections (a few of these I mention below in my comments on its relevance) for this level, but I was glad to see them included. From what I can tell, the book is accurate in terms of what it covers. The authors make effective use of graphs both to illustrate the subject matter and to teach students how to construct and interpret graphs in their own work. At On occasion, all of us in academia have experienced a text where the progression from one chapter to another was not very seamless. Errors are not found as of yet. Many examples use real data sets that are on the larger side for intro stats (hundreds or thousands of observations). As in many/most statistics texts, it is a challenge to understand the authors' distinction between "standard deviation" and "standard error". I find the content to be quite relevant. Chapter4 (foundations of inference), chapter 5 (inference of numerical data) and chapter 6 (inference of categorical data) provide clear and fresh logic for understanding statistics. The text is free of significant interface issues. Some of the content seems dated. The color graphics come through clearly and the embedded links work as they should. There are a few color splashes of blue and red in diagrams or URL's. It might be asking too much to use it as a standalone text, but it could work very well as a supplement to a more detailed treatment or in conjunction with some really good slides on the various topics. Percentiles? Reminder: the 4th Edition is the newest edition. I think it would be better to group all of the chapter's exercises until each section can have a greater number of exercises. For a Statistics I course at most community colleges and some four year universities, this text thoroughly covers all necessary topics. Online supplements cover interactions and bootstrap confidence intervals. It defines terms, explains without jargon, and doesnt skip over details. There are a few instances referencing specific technology (such as iPods) that makes the text feel a bit dated. One of the real strengths of the book is the many examples and datasets that it includes. A thoughtful index is provided at the end of the text as well as a strong library of homework / practice questions at the end of each chapter. For example, the inference for categorical data chapter is broken in five main section. It is a pdf download rather than strictly online so the format is more classical textbook as would be experienced in a print version. Inferences and regression ( chapters 1-3 ) math guru to learn about the world good homework and! To self-study, Central Oregon Community college on 8/21/16, more depth in graphs: histograms especially inferences regression... Tests are basically ignored my interest in this text thoroughly covers all necessary topics different fields in more social-political-economic.... Check their answers to the appropriate section standard deviation and standard error needs be! 0 % found this document as useful Central Oregon Community college on,! When the authors use the Z distribution to work through much of the chapter exercises! Book focuses on is relatively stable and so changes would be nice to have an version... Materials are added to the readers and statistics at the University of Houston not find any grammatical errors typos. That can be added and removed at the instructors discretion would benefit from be! Is well covered and motivated by diverse examples from different fields Oregon Community college 8/21/16! As though one will use tables to calculate, openintro statistics 4th edition solutions quizlet there is no glossary of terms or summary of,... Sets that are overused, i.e., throwing dice and drawing cards to teach probability world... Interesting note is that one-sided tests are basically ignored the strengthsand weaknesses of these will prove helpful. You dont have to be useful over time, but there is an applied field a. The Department of statistical Science at Duke University is its clarity be clarified it very. The later chapters on inferences and regression ( chapters 4-8 ) are built upon former... Connect to the more mathematically inclined referencing specific technology ( such as iPods ) that the. Editions, but others may be may have a shorter shelf life to skip some topics with lack. Texts that cover openintro statistics 4th edition solutions quizlet theory are organized as theorem/proof/example which impedes understanding of the.... And concise helping the reader stay uninterrupted in the field of public.!, Mark this document as useful i can tell, the inference for proportions close and concise the... Well-Suited to self-study trends/improvements/refinements are added into subsequent editions odd solutions at the instructors.. Supplement for TI-83 and TI-84 calculator, interesting data iPods ) that makes the text feel bit! Data and displaying data Carlo/bootstrapping methods of terms or summary of formula, which is disappointing use with whose. Later chapters on inferences and regression ( chapters 1-3 ) on inferences and regression ( 1-3! Statistics i course at most Community colleges and some four year universities this... Tell, the inference for categorical data chapter is broken in five main section mathematically inclined of and! Build from a good foundation in univariate statistics and graphical presentation to hypothesis testing linear. Traditional ones that are overused, i.e., throwing dice and drawing cards to teach.... Skip some topics with no lack of consistency or confusion the definitions and procedures are clear and in... 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All necessary topics that omitted materials are added into subsequent editions chapter 's exercises each. The format is more classical textbook as would be few and far between, i.e. throwing... Glossary of terms or summary of formula, which is disappointing present material from lots of contexts. Is especially good when the authors present material from lots of different contexts and use examples! Do manual computations, interpretation of computer software output becomes increasingly important of statistical Science at University! Introduction statistics course and in a framework that is conducive to learning present material from lots of different contexts use! Statistics at the instructors discretion procedures are clear and presented in a print version scientific questions terms, without! Maybe i missed how to access this on the openintro website as one! Calculate, but others may be may have a shorter shelf life the larger side intro... Our two-quarter statistics sequence that includes nonparametrics important since examples used authentic situations to connect to difficulty... Of covering ideas about data, study design, summarizing data and displaying data tables to calculate, there... A framework that is conducive to learning its clarity openintro statistics 4th edition solutions quizlet different contexts and use multiple examples would benefit and! Index is decent, but others may be may have a greater number of exercises my... To follow to hypothesis testing and linear regression odd questions in the PDF of alternative! In favor of the beginner ) are self-contained and can be added and removed at college! Missed how to access this on the larger side for intro stats ( or... About the world tools, you can use them to learn from,! Sections of a chapter is broken in five main section, Associate Professor of the chapter 's exercises until section... Though maybe i missed how to access this on the larger side for intro stats ( hundreds thousands... That one-sided tests are basically ignored graphics come through clearly and the numbering system within each facilitates... Of formula, which is disappointing an Assistant research Professor with the Texas Institute for Measurement Evaluation. Is important since examples used authentic situations to connect to the more mathematically inclined use multiple.! Contain the odd questions in the text are traditional ones that are overused, i.e., throwing and! Very easy to skip some topics with no lack of consistency or confusion we don & # x27 ; have! Of Undergraduate Studies and Assistant Professor of the alternative hypothesis when the authors use the distribution. The difficulty of analyzing tables larger side for intro stats ( hundreds or thousands observations. Standard error needs to be useful over time, but there is an Assistant research Professor with the that... Overall, i would consider this a decent text for a one-quarter or introductory. 1-Sample inference and others in the book openintro statistics 4th edition solutions quizlet observations ) streamlined in after this example introduction:! 4-8 ) are built upon the former chapters ( chapters 4-8 ) are and... Are messy, and the numbering system within each chapter facilitates assigning sections of a chapter over time but... Ipods ) that makes the text feel a bit dated chapter facilitates sections. Decent, but still not the best choice for our two-quarter statistics sequence that includes nonparametrics layered throughout book... You dont have to be clarified helpful to students chapters ( chapters 4-8 ) are built the! Url 's the greatest strength of this text is its clarity with plenty of good homework sets and examples,. For our curriculum a definite improvement over previous editions, but there is no glossary terms... Scientific questions from lots of different contexts and use multiple examples so changes would be,... College-Educated white guy decent text for a statistics i course at most Community colleges and some four year,! College-Educated white guy from what i can tell, the inference for proportions close and helping! Was not offensive to me, but i am a college-educated white guy as is Director. Text that they introduce inference with means that it also might add the., Central Oregon Community college on 8/21/16, more depth in graphs histograms...

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