Africa fourth edition pdf download

Oxford school atlas pdf download — Hello Everyone, in this article we will discuss about the oxford atlas pdf book. This book is one of the best books for the detailed study and understanding of maps. This provides comprehensive coverage of the continents including thematic features of each continent, and regional maps of countries and regions.

Includes separate physical and political maps of India and the continents. As we all know in competitive exams some questions are also cover from the maps section.

Here, we will provide you the English version of oxford atlas book. I feel that the greatest strength of this text is its clarity. The simple mention of the subject "statistics" can strike fear in the minds of many students. 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. Well, this text provides a kinder and gentler introduction to data analysis and statistics.

While the authors don't shy away from sometimes complicated topics, they do seem to find a very rudimentary means of covering the material by introducing concepts with meaningful scenarios and examples. On occasion, all of us in academia have experienced a text where the progression from one chapter to another was not very seamless.

This is especially true when there are multiple authors. I did not see any issues with the consistency of this particular textbook. In fact, I could not differentiate a change in style or clarity in any sections of this text. The authors used a consistent method of presenting new information and the terminology used throughout the text remained consistent. This is sometimes a problem in statistics as there are a variety of ways to express the similar statistical concepts. This can be particularly confusing to "beginners.

While to some degree the text is easily and readily divisible into smaller reading sections, I would not recommend that anyone alter the sequence of the content until after Chapters 1, 3, and 4 are completed. Materials in the later sections of the text are snaffled upon content covered in these initial chapters. The authors point out that Chapter 2, which deals with probabilities, is optional and not a prerequisite for grasping the content covered in the later chapters.

After much searching, I particularly like the scope and sequence of this textbook. As aforementioned, the authors gently introduce students to very basic statistical concepts. 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 introductory material then serves as the foundation for later chapter where students are introduced to inferential statistical practices.

The authors use a method inclusive of examples noted with a Blue Dot , guided practice noted by a large empty bullet , and exercises found at end of each chapter. I find this method serves to give the students confidence in knowing that they understand concepts before moving on to new material. 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.

In some instances, various groups of students may be directed to certain chapters, while others hone in on that material relevant to their topic. 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. The document was very legible. The graphs and diagrams were also clear and provided information in a way that aided in understanding concepts.

This was not necessarily the case with some of the tables in the text. 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. I did not view an material that I felt would be offensive. The material was culturally relevant to the demographic most likely to use the text in the United State.

This is important since examples used authentic situations to connect to the readers. While the examples did connect with the diversity within our country or i. The text would surely serve as an excellent supplement that will enhance the curriculum of any basic statistics or research course.

While the text could be used in both undergraduate and graduate courses, it is best suited for the social sciences. 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.

I think that the book is fairly easy to read. The authors bold important terms, and frequently put boxes around important formulas or definitions. If anything, I would prefer the book to have slightly more mathematical notation. I did not see any problems in regards to the book's notation or terminology.

It appears smooth and seamless. The book is broken into small sections for each topic. Any significant rearranging of those sections would be incredibly detrimental to the reader, but that is true of any statistics textbook, especially at the introductory level: Earlier concepts provide the basis for later concepts.

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. For example, the Central Limit Theorem is introduced and used early in the inference section, and then later examined in more detail. I would tend to group this in with sampling distributions.

Also, for how the authors seem to be focusing on practicalities, I was somewhat surprised about some of the organization of the inference sections. The authors use the Z distribution to work through much of the 1-sample inference. The t distribution is introduced much later. I realize this is how some prefer it, but I think introducing the t distribution sooner is more practical. The organization in chapter 5 also seems a bit convoluted to me.

The chapter is about "inference for numerical data". 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.

It strikes me as jumping around a bit. Overall the organization is good, so I'm still rating it high, but individual instructors may disagree with some of the order of presentation. In general I was satisfied. 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. I assume this is for the benefit of those using mobile devices to view the book, but scrolling through on a computer, the sections and the exercises tend to blend together.

Some more separation between sections, and between text vs. 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. In addition to the above item-specific comments:.

I think that the first chapter has some good content about experiments vs. Better than most of the introductory book that I have used thus far granted, my books were more geared towards engineers.

Some of the sections have only a few exercises, and more exercises are provided at the end of chapters. This is similar to many other textbooks, but since there are generally fewer section exercises, they are easy to miss when scrolling through, and provide less selection for instructors. I think it would be better to group all of the chapter's exercises until each section can have a greater number of exercises.

I do not think that the exercises focus in on any discipline, nor do they exclude any discipline. This could be either a positive or a negative to individual instructors. I think in general it is a good choice, because it makes the book more accessible to a broad audience. That being said, I frequently teach a course geared toward engineering students and other math-heavy majors, so I'm not sure that this book would be fully suitable for my particular course in its present form with expanded exercise selection, and expanded chapter 2, I would adopt it almost immediately.

The book covers the essential topics in an introductory statistics course, including hypothesis testing, difference of means-tests, bi-variate regression, and multivariate regression. The authors make effective use of graphs both to illustrate the 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.

Examples from a variety of disciplines are used to illustrate the material. The discussion of data analysis is appropriately pitched for use in introductory quantitative analysis courses in a variety of disciplines in the social sciences. However, to meet the needs of this audience, the book should include more discussion of the measurement key concepts, construction of hypotheses, and research design experiments and quasi-experiments. These are essential components of quantitative analysis courses in the social sciences.

The book covers familiar topics in statistics and quantitative analysis and the presentation of the material is accurate and effective. One of the real strengths of the book is the many examples and datasets that it includes. Some of these will continue to be useful over time, but others may be may have a shorter shelf life.

In particular, examples and datasets about county characteristics, elections, census data, etc, can become outdated fairly quickly. Given that this is an introductory textbook, it is clearly written and accessible to students with a variety of disciplinary backgrounds.

The purpose of the course is to teach students technical material and the book is well-designed for achieving that goal.

Like most statistics books, each topic builds on ones that have come before and readers will have no trouble following the terminology as they progress through the book. One of the real strengths of the book is that it is nicely separated into coherent chapters and instructors would will have no trouble picking and choosing among them. For example, the authors have intentionally included a chapter on probability that some instructors may want to include, but others may choose to excludes without loss of continuity.

The book does build from a good foundation in univariate statistics and graphical presentation to hypothesis testing and linear regression. There are separate chapters on bi-variate and multiple regression and they work well together. The chapter on hypothesis testing is very clear and effectively used in subsequent chapters.

The formatting and interface are clear and effective. There are lots of graphs in the book and they are very readable. There are also pictures in the book and they appear clear and in the proper place in the chapters.

The authors present material from lots of different contexts and use multiple examples. They have done an excellent job choosing ones that are likely to be of interest to and understandable by students with diverse backgrounds.

The supplementary material for this book is excellent, particularly if instructors are familiar with R and Latex. The code and datasets are available to reproduce materials from the book. And, the authors have provided Latex code for slides so that instructors can customize the slides to meet their own needs.

For a Statistics I course at most community colleges and some four year universities, this text thoroughly covers all necessary topics. For example, types of data, data collection, probability, normal model, confidence intervals and inference for For example, types of data, data collection, probability, normal model, confidence intervals and inference for single proportions.

The content is accurate in terms of calculations and conclusions and draws on information from many sources, including the U. Census Bureau to introduce topics and for homework sets. Errors are not found as of yet.

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. For example, a scatterplot involving the poverty rate and federal spending per capita could be updated every year.

Another example that would be easy to update and is unlikely to become non-relevant is email and amount of spam, used for numerous topics.

The probability section uses a data set on smallpox to discuss inoculation, another relevant topic whose topic set could be easily updated. This selection of topics and their respective data sets are layered throughout the book.

The book uses relevant topics throughout that could be quickly updated. 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. The text meets students at a nice place medium where they are challenged with thoughtful, real situations to consider and how and why statistical methods might be useful. For example, a goodness of fit test begins by having readers consider a situation of whether or not the ethnic representation of a jury is consistent with the ethnic representation of the area.

The introduction of jargon is easy streamlined in after this example introduction. Notation is consistent and easy to follow throughout the text. Tables and graphs are sensibly annotated and well organized. Distributions and definitions that are defined are consistently referenced throughout the text as well as they apply or hold in the situations used.

Each chapter consists of sections. These sections generally are all under ten page in total. This easily allow for small sets of reading on a class to class basis or larger sets of reading over a weekend. Each section within a chapter build on the previous sections making it easy to align content. For example, the inference for categorical data chapter is broken in five main section. Single proportion, two proportions, goodness of fit, test for independence and small sample hypothesis test for proportions.

This keeps all inference for proportions close and concise helping the reader stay uninterrupted in the topic. The topics are presented in a logical order with each major topics given a thorough treatment. The text begins with data collection, followed by probability and distributions of a random variable and then finishing for a Statistics I course with inference. Perhaps an even stronger structure would see all the types of content mentioned above applied to each type of data collection. That is, do probability and inference topics for a SRS, then do probability and inference for a stratified sample and each time taking your probability and inference ideas further so that they are constantly being built upon, from day one!

Navigation as a PDF document is simple since all chapters and subsection within the table of contents are hyperlinked to the respective section. Graphs and tables are clean and clearly referenced, although they are not hyperlinked in the sections. The only visual issues occurs in some graphs, such as on page , which have maps of the U.

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. For example, income variations in two cities, ethnic distribution across the country, or synthesis of data from Africa.

The book has a great logical order, with concise thoughts and sections. While section are concise they are not limited in rigor or depth as exemplified by a great section on the "power" of a hypothesis test and numerous case studies to introduce topics. The reading of the book will challenge students but at the same time not leave them behind. Overall I like it a lot. The best statistics OER I have seen yet. More depth in graphs: histograms especially.

The most accurate open-source textbook in statistics I have found. Though I might define p-values and interpret confidence intervals slightly differently. I did not see much explanation on what it means to fail to reject Ho. I would consider this "omission" as almost inaccurate.

Although accurate, I believe statistics textbooks will increasingly need to incorporate non-parametric and computer-intensive methods to stay relevant to a field that is rapidly changing. Also, as fewer people do manual computations, interpretation of computer software output becomes increasingly important. Quite clear. The text, though dense, is easy to read. More color, diagrams, photos? Great job overall. However, the introduction to hypothesis testing is a bit awkward this is not unusual.

Create a clear way to explain this multi-faceted topic and the world will beat a path to your door. No problems, but again, the text is a bit dense.

More color, diagrams, etc.? Overall it was not offensive to me, but I am a college-educated white guy. Examples of how statistics can address gender bias were appreciated. Overall, this is the best open-source statistics text I have reviewed.

Most contain glaring conceptual and pedagogical errors, and are painful to read don't get me started on percentiles or confidence intervals. Also, a reminder for reviewers to save their work as they complete this review would be helpful. The coverage of this text conforms to a solid standard very classical semester long introductory statistics course that begins with descriptive statistics, basic probability, and moves through the topics in frequentist inference including basic Worlds Together, Worlds Apart is organized around major world history stories and themes: the emergence of cities, the building of the Silk Road, the spread of major religions, the spread of the Black Death, the Age of Exploration, alternatives to nineteenth-century capitalism, the rise of modern nation-states and empires, and others.

The Fourth Edition of this successful text has been streamlined, shortened, and features a new suite of tools designed to help students think critically, master content and make connections across time and place.

Tignor Publisher : W. Beginning with the origins of humanity up to our current times, this leading group of world historians tells the history of the world through a series of transformative stories: Out of Africa, the Axial Age, the building of the Silk Road, the rise of the world's major universalising religions, the expansion of the Mongol Empire, the Black Death, the Spread of New World Silver, the Slave Trade, the Atlantic Revolutions, Nineteenth-Century Alternative Visions, Nations and Empires, Masses and Modernity, the Three-World Order, and Contemporary Globalism.

The law of relative or comparative advantage states that two countries will benefit from trade if the opportunity costs of production or relative prices differ between the two countries.

South African citizens would be better off economically if the country did not engage in international trade at all. Statements 3 to 8 are based on the following information: Susan can knit 4 jerseys or sew 8 dresses per week, while Jackie can knit 3 jerseys or sew 4 dresses per week. Susan has an absolute advantage in knitting jerseys. Susan has an absolute advantage in sewing dresses. Susan has a relative or comparative advantage in knitting jerseys.

Susan has a relative or comparative advantage in sewing dresses. Jackie has a relative or comparative advantage in knitting jerseys. Jackie should specialise in knitting jerseys while Susan should specialise in sewing dresses. Absolute advantage is a prerequisite for trade. Equal advantage is a prerequisite for trade. Comparative or relative advantage is a prerequisite for trade. If South Africa could produce all goods at a lower cost per unit than Zimbabwe, South Africa would not trade with Zimbabwe at all.

The more open a country's economy is, the more vulnerable it is to changes in economic conditions in other countries. Adam Smith argued that countries should try to be as self-sufficient as possible. One of the basic reasons for international trade is that all countries do not possess the same factors of production e. All economic activities which take place within the borders of a country are recorded in the balance of payments.