BASIC STATISTICS BOOK
cittadelmonte.info: Understanding Basic Statistics, 6th Edition (): Charles Henry Brase, Corrinne Pellillo Brase: Books. This is the first international edition of a successful textbook with an outstanding pedigree. It covers a wide range of statistical theory commonly taught in faculties . These are the best books for learning modern statistics—and they're all I always give the same answer: Read An Introduction to Statistical.
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The Book Presupposes No Advance Knowledge Of cittadelmonte.info Statistics Fully Covers The Syllabi Of Statistics Courses Running In Various Universities. The authors have made sure they clarify your basic statistics concepts along with measures of eloquent involving statistical analysis. This top statistics book. books. Agresti, A. & Finlay, B., Statistical Methods for the Social Sci- ences, 3th Edition. Prentice Population and sample are two basic concepts of statistics.
By Dheeraj Vaidya 2 Comments. Top Books. To be accurate you need to have the right knowledge to use the right tricks for calculating well. Well, we have listed top statistics books to help you excel with your statistical knowledge. One of the best introductory statistic books to help you get started with your knowledge at undergraduate level.
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 The text contains relevant information that is current and will not become outdated in the near future.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.
Top 11 Best Statistics Books
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.
Basic Statistics: A Modern Approach by Morris Hamburg
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.
Textbook of Basic Statistics
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.
The pdf appears somewhat sparse by comparison to publisher texts, lacking pictures, colored boxes, etc. But the on-line version has many active links providing definitions and graphic illustrations for key terms and topics. Most sections also have short videos that are professionally done, with narration and smooth graphics. In this way, the text is interactive and flexible, offering varied tools for students.
The text in pdf form appeared to free of grammatical errors, as did the on-line version, text, graphics and videos. This text contains no culturally insensitive or offensive content. The focus of the text is on concepts and explanation. The text would be a great resource for students. The full content would be ambitious for a 1-semester course, such use would be unlikely. The text is clearly geared towards students with no statistics background nor calculus.
The text could be used in two styles of course. For 1st year students early chapters on graphs and distributions would be the starting point, omitting later chapters on Chi-square, transformations, distribution-free and size effect chapters.
Alternatively, for upper level students the introductory chapters could be bypassed with the latter chapters then covered to completion. The e-book videos are an enabling tool if this approach is adopted.
This is a comprehensive book on statistical methods, its settings and most importantly the interpretation of the results. But the challenge is the But the challenge is the knowledge of how to set the case, setting parameters for example confidence intervals and knowing its implication on the interpretation of the results. If not done properly this could lead to deceptive inferences, inadvertently or purposely. This book does a great job in explaining the above using many examples and real world case studies.
The Best Statistics Books Of All-Time
If you are looking for a book to learn and apply statistical methods, this is a great one. I think the author could consider revising the title of the book to reflect the above, as it is more than just an introduction to statistics, may be include the word such as practical guide.
The contents of the book seems accurate. Some plots and calculations were randomly selected and checked for accuracy. The book topics are up to date and in my opinion, will not be obsolete in the near future. I think the smartest thing the author has done is, not tied the book with any particular software such as minitab or spss. Hardcover , pages. Published January 1st by Harcourt Brace Jovanovich. More Details Original Title. Other Editions 1.
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Lists with This Book. This book is not yet featured on Listopia. Community Reviews. Showing Rating details. More filters. Sort order. Aug 01, Dewey Norton rated it it was amazing. My third course in statistics, a great one taught by Professor Hamburg at Wharton, and the only good course in this field I ever took.
Calculus based. The key to my success was a marvelous secretary in the statistics department who, with Hamburg's approval, gave me the answer book to the questions in the textbook. There were about 40 questions at the end of each chapter. All I had to do was read the chapter, work all the problems, check my answers against Hamburg's and understand my mistakes.
On My third course in statistics, a great one taught by Professor Hamburg at Wharton, and the only good course in this field I ever took. Statistics came well before computers. It would be very different if it were the other way around. The stats most people learn in high school or college come from the time when computations were done with pen and paper.
There are better options.
Read An Introduction to Statistical Learning. Tibsharani is a coauthor of both. You can download them for free.
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