The annual reports of companies contain variety of data on sales, production, expenditure, inventories, capital …. Business Statistics, 4th Edition. Sharma Jan Vikas Publishing House. Buy as Gift. Add to Wishlist. Free sample. The fourth edition of Business Statistics builds upon the easy-to-understand, problem-solving approach that was the hallmark of the previous editions..
It aims to supplement textbooks on business statistics and upgrade the student's knowledge and skill in the subject. It is your responsibility to ensure that people understand your requests - so communicate clearly, and ask if people have understood what you are asking for. Treat everyone respectfully and courteously at all times. Particularly when there is a problem! Everyone who works for you is a valuable human being who deserves respect.
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But do you really need all this knowledge? There are hundreds of specializations in business and management; books covering all these domains certainly cannot be read by a human. However, among the others there are shining several must-read diamonds that will fit almost every business or management field of interest.
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Rockefeller and Thomas Edison. The history of America has made some people billionaires, but pushed some others down.
The story odf inequlity comes along with the multiple stories of heroic resistance. Those same racist structures and individuals remained intact after the end of the red line, and the close relationship between regulators and industry created incentives to ignore violations.
Dennis Kimbrough, observing how the severity of the ongoing housing and credit crisis disproportionately affects the African American community, gazes intently at a carefully educated group of people who have reached the heights of success and how others can emulate them. Starting new business requires a lot.
It requires patience, confidence, investments, persuasion. The text is appropriate in a 1st of 2 statistics courses. It does not cover non-linear regression as would be used to assess likelihood of outcome, it does not cover descriptive clustering, and it does not cover predictive segmentation. It also does not cover time-series analysis. As a result, it does not cover the techniques commonly employed in business. But it does provide the background necessary prior to learning and use of more advanced topics.
This book does not need to change for at least several hundred years. May be good forever, literally. Really clear, easy to understand. Nice diagrams and examples, many questions and exercises built in. Built to use Excel. World-class for a stats book. Very consistent and stays within its limits. Doesn't stray from introductory statistics using the Excel stats package. Flows in the order I would choose. Not need or benefit to cover in anything other than chapter order.
Very clear for a stats book, Questions seemed carefully worded to avoid misinterpretation. Of course, students are very clever when it comes to finding ways to misinterpret, so we'll see once I use it in class. Unless someone is professionally offended, and looking for ways to claim to be offended in order to further their career or notoriety, it is unlikely in my opinion they will find a fair, reasonable, and legitimate cause to be offended as a result of this text.
Reviewed by William M. It is purportedly designed for a one-semester course. For that at least relative to business students at UNO , it is too long -- and too long on the mathematics. For a For a two-semester course, at least for our purposes, it is too short.
For example, there is no discussion of 2-factor Anova, RBD, etc. However, there is much to admire about the way that the authors present the ideas. I spent about four hours reading various parts of the text and found no sign of bias or any gross errors. One can quibble over some of the definitions, e. I saw a typo or two -- e.
As with any book, there are probably others. But let me emphasize that I am not a professional statistician. Surprisingly, calculus techniques make an appearance toward the end of the book the average business student will have little or no idea of that. But, aside from some instructions for using Excel for regression analysis why not do this for Anova as well?
In the chapter on the F-distribution, where did those p-values come from? Or did I miss something? How is this text going to compete with those?
Overall, I like the breezy writing style. But it is a bit bipolar, occasionally almost patronizing and then rather technical. Some terms are used which the student audience has virtually no chance of understanding.
Better to omit those or provide explanation. On the other hand, since few students these days actually read books, particularly math books, anyway, why not let the authors express themselves in a way that they find logical and intellectually appealing?
My students depend on me to explain the material, or, if I fail them, YouTube. The text seemed terminologically consistent to me. I do recall a spot in the Anova section where the use of n nT? Introductory statistics is not a very modular sort of subject -- it is more a continuous development. For example, the concept of p-value is introduced in chapter 9 of virtually every stats text.
Otherwise, I liked the presentation given here in ch. The topics of the text are presented in the normal progression. There is some possibility of changing the order of presentation after hypothesis testing Ch. Once again, this is how introductory stats works. Interface is fine, although I absolutely hate scrolling through a pdf. Students would definitely want a print version.
Finally, the unscripted part of the review. There is a lot to like about this presentation of the subject. Some parts are quite enjoyable. Here are my criticisms, in order of my view of their increasing importance. The type-setting if that is the right term of the formulas in generally pretty lousy. For example, x-bar is always shown with the bar about a mile above the x.
The integral on p. Those formulas for r are terrible-looking. I always use MathType for this stuff. Many authors do this. Who, except programmers, cares how the computer does it? The definition formula offers insight.
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