This course is a short series of lectures on Introductory Statistics. Topics covered are listed in the Table of Contents. The notes were prepared by Ewa Paszek and Marek Kimmel. The development of this course has been supported by NSF grant. Partial Differential Equations. Mathematics for Computer Scientists. A Handbook of Statistics. Decision-Making using Financial Ratios. Understanding Statistics. Applied Statistics. Introductory Algebra.
Elementary Algebra and Calculus. An Introduction to Matlab. Mathematics Fundamentals. A youtube Calculus Workbook Part I.
Introduction to statistical data analysis with R. Introduction to Complex Numbers. Statistics for Business and Economics. Numerical Examples in Fuels and Energy.
Quantitative Analysis. Essential Mathematics for Engineers. Descriptive Statistics. Introduction to Vectors. Introductory Maths for Chemists. Elementary Algebra Exercise Book I. Mathematics - Free of Worries at the University I. Essentials of Statistics. Inferential Statistics. Elementary Linear Algebra: Part I. An Introduction to Abstract Algebra. Differential Equations for Engineers. Blast Into Math!
Demographic Statistics. Mathematical Modeling I - preliminary. It also has a formula review at the end of each chapter. I can imagine that these are heavily used by students when studying! Formulas are easy to find and read and are well defined. There are a few areas that I might have found frustrating as a student. For example, the explanation for the difference in formulas for a population vs sample standard deviation is quite weak. Again, this is a book that focuses on sort of a "black-box" approach but you may have to supplement such sections for some students.
This low rating should not be taken as an indicator of an issue with this book but would be true of virtually any statistics book. Different books still use different variable symbols even for basic calculated statistics. However, I think it would be possible to skip some chapters or use the chapters in a different order without any loss of functionality. This book uses a very standard order for the material.
The chapter on regressions comes later than it does in some texts but it doesn't really matter since that chapter never seems to fit smoothly anywhere.
There are numerous end of chapter problems, some with answers, available in this book. I'm vacillating on whether these problems would be more useful if they were distributed after each relevant section or are better clumped at the end of the whole chapter.
That might be a matter of individual preference. I found no errors. However, there were several sections where the punctuation seemed non-ideal. This did not affect the over-all useability of the book though. I'm not sure how well this book would work internationally as many of the examples contain domestic American references. However, I did not see anything offensive or biased in the book.
As the title implies, this is a brief introduction textbook. It covers the fundamental of the introductory statistics, however not a comprehensive text on the subject.
A teacher can use this book as the sole text of an introductory statistics A teacher can use this book as the sole text of an introductory statistics. The prose format of definitions and theorems make theoretical concepts accessible to non-math major students.
The textbook covers all chapters required in this level course. It is accurate; the subject matter in the examples to be up to date, is timeless and wouldn't need to be revised in future editions; there is no error except a few typographical errors. There are no logic errors or incorrect explanations. This text will remain up to date for a long time since it has timeless examples and exercises, it wouldn't be outdated.
The information is presented clearly with a simple way and the exercises are beneficial to follow the information. The material is presented in a clear, concise manner. The text is easy readable for the first time statistics student. The structure of the text is very consistent. Topics are presented with examples, followed by exercises. Problem sets are appropriate for the level of learner.
When the earlier matters need to be referenced, it is easy to find; no trouble reading the book and finding results, it has a consistent scheme. This book is set very well in sections. There is no logic errors and incorrect explanations, a few typographical errors is just to be ignored.
This book is pretty comprehensive for being a brief introductory book. This book covers all necessary content areas for an introduction to Statistics course for non-math majors. The text book provides an effective index, plenty of exercises, The text book provides an effective index, plenty of exercises, review questions, and practice tests. It provides references and case studies. The glossary and index section is very helpful for students and can be used as a great resource.
Content appears to be accurate throughout. Being an introductory book, the book is unbiased and straight to the point. The terminology is standard. The content in textbook is up to date. It will be very easy to update it or make changes at any point in time because of the well-structured contents in the textbook. The author does a great job of explaining nearly every new term or concept. The book is easy to follow, clear and concise.
The graphics are good to follow. The language in the book is easily understandable. I found most instructions in the book to be very detailed and clear for students to follow. Overall consistency is good. It is consistent in terms of terminology and framework. The writing is straightforward and standardized throughout the text and it makes reading easier. The authors do a great job of partitioning the text and labeling sections with appropriate headings.
The table of contents is well organized and easily divisible into reading sections and it can be assigned at different points within the course. Overall, the topics are arranged in an order that follows natural progression in a statistics course with some exception. They are addressed logically and given adequate coverage. The text is not culturally insensitive or offensive in any way most of time. Some examples might need to consider citing the sources or use differently to reflect current inclusive teaching strategies.
Overall, it's well-written and good recourse to be an introduction to statistical methods. Some materials may not need to be covered in an one-semester course.
Various examples and quizzes can be a great recourse for instructor. The text includes the introductory statistics topics covered in a college-level semester course.
An effective index and glossary are included, with functional hyperlinks. The content of this text is accurate and error-free, based on a random sampling of various pages throughout the text. Several examples included information without formal citation, leading the reader to potential bias and discrimination. These examples should be corrected to reflect current values of inclusive teaching.
The text contains relevant information that is current and will not become outdated in the near future. The statistical formulas and calculations have been used for centuries.
The examples are direct applications of the formulas and accurately assess the conceptual knowledge of the reader. The text is very clear and direct with the language used. Graphs, tables, and visual displays are clearly labeled. The terminology and framework of the text is consistent.
The hyperlinks are working effectively, and the glossary is valuable. Each chapter contains modules that begin with prerequisite information and upcoming learning objectives for mastery. The modules are clearly defined and can be used in conjunction with other modules, or individually to exemplify a choice topic. With the prerequisite information stated, the reader understands what prior mathematical understanding is required to successfully use the module. I think this rearranged version of the index would better align with current Introductory Statistics texts.
The structure is very organized with the prerequisite information stated and upcoming learner outcomes highlighted. Each module is well-defined. Adding an option of returning to the previous page would be of great value to the reader.
While progressing through the text systematically, this is not an issue, but when the reader chooses to skip modules and read select pages then returning to the previous state of information is not easily accessible. Several examples contained data that were not formally cited. These examples need to be corrected to reflect current inclusive teaching strategies.
An included solutions manual for the exercises would be valuable to educators who choose to use this text. As a text for an introductory course, standard topics are covered. It was nice to see some topics such as power, sampling, research design and distribution free methods covered, as these are often omitted in abbreviated texts. Each module Each module introduces the topic, has appropriate graphics, illustration or worked example s as appropriate and concluding with many exercises.
A comprehensive glossary provides definitions for all the major terms and concepts. The case studies give examples of practical applications of statistical analyses. Many of the case studies contain the actual raw data. To note is that the on-line e-book provides several calculators for the essential distributions and tests.
These are provided in lieu of printed tables which are not included in the pdf. Such tables are readily available on the web. The content is accurate and error free.
Notation is standard and terminology is used accurately, as are the videos and verbal explanations therein. Online links work properly as do all the calculators. The text appears neutral and unbiased in subject and content. The text achieves contemporary relevance by ending each section with a Statistical Literacy example, drawn from contemporary headlines and issues.
Of course, the core topics are time proven. The text is very readable. Meanwhile for this same content the on-line version appears streamlined, uncluttered, enhancing the value of the active links. This terminology and symbol use are consistent throughout the text and with common use in the field. The pdf text and online version are also consistent by content, but with the online e-book offering much greater functionality.
The chapters and topics may be used in a selective manner. Certain chapters have no pre-requisite chapter and in all cases, those required are listed at the beginning of each module.
It would be straightforward to select portions of the text and reorganize as needed. The online version is highly modular offering students both ease of navigation and selection of topics. Chapter topics are arranged appropriately. In an introductory statistics course, there is a logical flow given the buildup to the normal distribution, concept of sampling distributions, confidence intervals, hypothesis testing, regression and additional parametric and non-parametric tests.
The normal distribution is central to an introductory course. Necessary precursor topics are covered in this text, while its use in significance and hypothesis testing follow, and thereafter more advanced topics, including multi-factor ANOVA. Each chapter is structured with several modules, each beginning with pre-requisite chapter s , learning objectives and concluding with Statistical Literacy sections providing a self-check question addressing the core concept, along with answer, followed by an extensive problem set.
The clear and concise learning objectives will be of benefit to students and the course instructor. No solutions or answer key is provided to students. The on-line interface works well.
In fact, I was pleasantly surprised by its options and functionality. This discipline is present in many areas of public life. Thanks to it, indispensable data is obtained to understand the realities of the world.
Become an expert in this branch of mathematics by studying our books on statistics. Statistics can be defined as the discipline that studies, collects, analyzes and describes a set of data. This data is then compared with other data to obtain a complete result. Among its most relevant uses is the study of a specific population or sample, to see how it has evolved or how it can provide a solution to a given problem.
Statistics can be divided into descriptive statistics describes the characteristics of a data set , inferential statistics uses methods to make predictions and generalizations , parametric statistics works on the hypothesis of the distribution of the data and nonparametric statistics does not assume that the data have a specific type of distribution.
This important discipline could not fail to have a section of more than 20 books of statistics in PDF.
Learn all about the subject and download our titles right now on your electronic devices. Fuente: Online Stat Book. Fuente: Arizona Math. Fuente: University of Toronto.
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