statistics for veterinary and animal science Reviews & Opinions
Submit statistics for veterinary and animal science review or read customer reviews:
100 Reviews Found
Watch statistics for veterinary and animal science video reviews and related movies:
See Statistics for Veterinary and Animal Science on youtube.
See Statistics for Veterinary and Animal Science on youtube.
See Statistics for Veterinary and Animal Science, Second Edition on youtube.
See CHOOSING A PRE-VET MAJOR: How to get into Veterinary School Episode 3 on youtube.
See Biostatistics for Animal Science An Introductory Text on youtube.
See Mental Health Statistics Vary in Veterinary Profession on youtube.
See AGRICULTURE STATISTICAL SCIENCE OBJECTIVE MCQ QUESTION PART -2 FOR ICAR JRF, BHU, AAO, AO, SRF, on youtube.
See Documentary on Faculty of Veterinary & Animal Science,SAU on youtube.
Scroll down to see all opinions ↓
This book is an eye-opener as to some of the ways our info is taken from us and being used. Some of the ways featured in this book I had absolutely no clue that was happening. I mean we have all noticed that if we look something up on Google, that following that Fb starts to use ads targeting something we are already interested in. This is a amazing book to read if you wish to know how and why your info is taken and used.
I emphatically suggest this book for your business based library. The point by point models and straightforward language truly helped me and it created measurements, a troublesome topic to grasp and vanquish, so natural for me. On the off possibility that you need to begin settling on extreme business choices depending on figures and numbers, this total apprentice's manual for factual science will carry extraordinary preferred position to you.
This book has a lot of potential. It was interesting and presented a lot of true life examples of statistics used for iffy purposes. However, it was also poorly written, inconsistent, full of rambling tangents, and displayed the author’s biases and blindnesses- most notably a barely concealed racist streak as well as a seemingly deeply ingrained misogyny, which miscolored several sections among which the two most blatant are the wage gap, and alimony. He has filled his book with numerous private opinions and generalizations, such as the wage gap is made because women are more likely to take a vacation than men (!) without a single source to back up his claims. In fact, most of the examples he points out throughout the entire book contain just enough to state his claim then conclude without any justification. If this were a debate article or a paper on persuasion it would have gotten an an F.Even excluding the sections where sexist and racist undercurrents can be found (the sections with the most rambling, I might add), the book needs a lot of revising and would benefit greatly from a co-author with other perspectives as well as a background in writing science a globe where ”just a small learning is a risky thing”, the author of this book should know better than to leave impressionable readers with his dogmatic, authoritative opinions rather than logical, consistent conclusions backed up with actual sources described within the paragraph. This is deliciously ironic considering the main idea of the book is how statistics can be misleading when not all the info is presented or explained clearly.I actually think this book started off with noble intentions and then got too broad and out of control so I am giving it 3 stars instead of the 2 that it would otherwise deserve.I received a free copy of this book via Booksprout and am voluntarily leaving a review.
If you just look at the title of this book, you might be led to believe that it might support you with your Probability and Statistics class. But another look at the subtitle suggests that this book is not meant to aid academic studies—as well as revealing a certain bias about statistics. I would agree with the author that statistics may be manipulated to say whatever a person or organization wants them to say. However, this particular book is unfocused in its discussion of statistics. The introductory parts of the book don’t seem to have much to do with statistics at all, or at least with the author is trying to present is not done so that the inferences can be clearly drawn. The core of the book aims to look at specific segments of society or academia and how they use and abuse statistics; laws and criminality, business, social sciences, and politics. However, the first case he looks at in a criminology section has more to do with business than law. Each of the cases or concepts that he looks at aren’t written in a tightly cohesive fashion to create them more easily understood by the reader.I think the book required a general editor to support the author focus the entire book as well as the sections of it. The book is also in serious need of a copyeditor or proofreader, as a lot of primary rules of grammar and punctuation seem to be unknown to or disregarded by the author.I believe this is a worthwhile subject for a book. Its promise, however, was not realized by this author.I received a free copy of this book, but that did not affect my review--obviously!
Being in a globe where technology rules, we don't realize what is going on in the background. I mean sure you have conspiracy theorists that believe Alexa works for the CIA and such. But in reality everything we do is being monitored in some method or function. This book is an eye-opener as to some of the ways our info is taken from us and being used. Some of the ways featured in this book I had absolutely no clue that was happening. I mean we have all noticed that if we look something up on Google, that following that Fb starts to use ads targeting something we are already interested in. This is a amazing book to read if you wish to know how and why your info is taken and used.
This book makes it easier to understand how everything we see including statistics can't always be believed. Data can be manipulated or biased on order to achieve certain results....the audiobook gives a peek into this phenomena...is was enjoyable and entertaining...would recommend to anyone just for the sake off information
First, allow me note that I have bachelor's degree in Math, and I have worked in a statistics-related field for the past 15 years. Which is to say that I am comfortable with complex mathematics, but it has been a while since my formal education, and some parts of my training have gotten a small rusty over the years.I was looking for a book that would refresh my memory a bit on linear algebra, particularly for the use of matrix calculations in statistics. This is the third book that I have tried in order to accomplish that goal. The first book that I tried was Poole's Linear Algebra textbook. While the level of this wasn't too difficult, its coverage was too broad for the specific goal that I had in mind (I didn't love it as a self-learning, or rather self-refreshing, textbook either). Next I tried "Matrix Algebra" by Gentle. I suspect that this will be a book that I like to go back to for reference, as it is very thorough and rigorous, but it was a nightmare to test to learn from. Finally, I found Linear Algebra and Matrix Analysis for Statistics (LAMAS) by Banerjee and Roy. Based on the title, I was hopeful that this book would be more focused on the subject that I was interested in, and the flap description - which touted starting at the basics and then heading into complex matters - sounded just right for me.I'm finding that I have a small bit of a love/hate relationship with this book. First: the good. After striking out twice before finding this book, I'm really enjoying the overall flow of the instruction and the chapters. Subjects are brought up in what seems like a logical order, and time is taken to build an understanding before moving on to the next subject. Most Linear Algebra texts are going to have a chapter or two at the beginning explaining the fundamentals of vectors and matrix math, but often the books just list the basics and then jump right into the complex stuff. Another frustration I have with a lot of upper-level math texts is that the authors often think that just showing a formula is enough to give the reader understanding. Yes, I can reason through what a formula is saying, but for me (especially given the growing years since my latest math class) I search it much easier to learn when I can see that formula in action with actual numerical examples (this was one of my frustrations with Gentle). In LAMAS, the authors don't just list the primary functions of vectors and matrices. They spend time explaining the basics and then give numerical examples to support you work through the formulas. And because of the intelligent flow of the book, you begin out doing primary examples, but before you know it you're doing more complex things. In terms of a book helping me self-(re)learn Linear Algebra, especially matrix math for statistics, this is exactly what I was looking e bad: the editor really dropped the ball with this book. There is a decent number of mostly-harmless punctuation and grammar errors (e.g., "Each step of the Gauss-Jordan way forces the pivot to be equal to 1, and then annihilates all entries above and below the pivot are annihilated." - pg 43), but the real crime is that there are sometimes errors in the formulas. Some of these are simple to spot (e.g., "Left-hand distributive law: Allow A be an m*p matrix, B and C both be p*n matrices. Then, A(B+C) = AB + BC." - pg 12), others are not. For example, when using the Type III Elementary Matrix formula on page 46, the respond that I obtain when working through the example is always the transpose of the respond shown in the book. The respond shown in the book is correct; I suspect that an i and a j have been switched somewhere in the formula (it's possible that I'm doing something wrong, though I've worked it through several times, but once a book shows a propensity for error in a formula, you never know if the problem is your own understanding or a typo in the book). One latest example: when discussing Crout's Algorithm on page 71, when talking about the u vectors and the l vectors, the book uses the subscript i to refer to rows and j to refer to columns, as it always had up to that point in the book. When giving the generalized formulas at the bottom of the page, it starts with Uij = ..., keeping the same convention. Then it states Lji = .... At this point I wasn't sure if they just decided to switch the order of how things were shown or what, but after working through the example, it turns out that, just for this formula, j refers to the row and i refers to the column, for whatever reason. Another annoyance is that, while there are issues at the end of each chapter to support reinforce the learning, there are no answers given for any of some ways, I feel like this is actually making me learn the subjects better, as I am having to pay very close attention to the info and work through every example either by hand or in Excel. Still, it's no method to write a textbook. In this respect, it's helpful to have Gentle's book on hand to cross-check some of the formulas (though he tends to use various notation). All in all, I still like this book, and I am still finding it the most helpful for me for re-learning the material. Once I know the material I will probably use Gentle's book for reference. With a more careful editor, this could be a amazing book. I bet the second edition will be wonderful.***Update: I wrote the first part of this review before finishing the book (which, in retrospect, was a poor idea), and I found myself getting more frustrated with the book as I progressed. First, one of the things that I praised the book for in the first review (giving numerical examples) almost entirely went away in the back half of the book. Second, and more frustrating for me, the book never actually created the connection between the linear algebra and the statistics. Thus, without numerical examples, and without directly making the connection to statistics, you're left with "This is a such-and-such matrix: [gives mathematical definition]. This is a such-and-such transformation of the matrix: [gives formula]. Based on these definitions, here's Lemma 5.3...." This is precisely the kind of approach that created me give up on Gentle. If you don't give me any info about what the actual functional uses of these things are (preferably with numerical examples), then it becomes a true grind to work through. And even if you do work through it to test to understand it, you're not really sure what you just learned because no app in statistics is given. Even more tantalizing, the authors frequently say things like, "...this is a critical conclusion [or process, or definition, or transformation, etc.] for Linear Algebra with a lot of uses." Great! Please tell me where. The title of this book, after all, does say "...For Statistics"!I began to fear that this was not the book I was hoping it would be in the chapter titled "More on Orthogonality." In that chapter the authors mentioned the normal equations, which I was already familiar with, and I was surprised to search that they didn't discuss the connection to regression equations. Then, at the end of the chapter they state, "Orthogonality, orthogonal projections and projectors, as discussed in this chapter and Chapter 7, play a central role in the theory of statistical linear regression models.... While it is tempting to discuss the attractive theory of statistical linear models, which brings together probability theory and linear algebra, we opt not to pursue that route in order to maintain our focus on linear algebra and matrix analysis." (pg 252-253) If that is the case, then I want that they had just titled the book, "Linear Algebra and Matrix Analysis." I won't change my rating just because the book didn't meet my specific needs, although I do search the title misleading. I guess my find continues...
Given the absence of references to actual statistical ideas in the text, this is a badly misnamed book. I would have done as well or better to use a text that didn't implicitly promise a statistically oriented e editing is sloppy or possibly simply wasn't done. The errata were not simple to search and were also dreadfully incomplete: lots of errors in subscripts etc. that often create it difficult to follow. Would not buy again.
I have a Bachelors in Computer Science and am currently pursuing an MS with emphasis on statistical data mining and modeling. While I had exposure to undergraduate linear algebra from the text by Gilbert Strang, I was looking for a text that would support me obtain a sound grasp of the subjects in linear algebra that would be most relevant for statistical modeling and data d to other texts of a related flavor, I found this to be exactly what I was looking for. The book is beautifully written and what is especially beautiful to me is that every theorem is proved in detail and, often, using various approaches. A lot of of the proofs given are much more elegant and clean than what I have seen in my earlier courses (e.g. proofs on equality of row and column ranks are revisited from various angles). Certain subjects such as rank factorization, oblique projectors, orthogonal projectors and positive definite matrices are covered in much greater detail than in other texts. Another nice feature of the book is that algorithms for matrix computations are explained in adequate detail although not quite at the level of specialized texts such as Golub and Van Loan.On the negative side, I agree with the other review that there are some typos although they are mostly obvious and not summary, a truly special text that covers a wide range of subjects with rigor and elegance at an intermediate level. It is at a level somewhere between the undergraduate applied linear algebra texts and the more formal matrix analysis texts targeted for mathematicians.
The very first R code example at the end of Chapter 2 is deprecated...no longer supported. Not a huge deal as this is a text and I expected the book's student resources www service to have the updated code. Nope. So, if you're looking for a book that has code you can run with respect to examples this is not it (without a major hassle and considerable time and effort, anyway). To be fair, this was the first example, but I'm not overly confident that I won't be wasting more of my time with subsequent coding in later chapters.
This book is the text for a graduate course in Geography. We have been through several chapters. The chapters are short and filled with perfect information, but at times the explanation could be more thorough. Having the R code and data (available from the companion website!) is extremely helpful in that it allows students to understand concepts and their implementations.
amazing resource for those wanting to provide hospice or palliative care for pets. We are starting a program within a municipal shelter and this is a amazing resource and there are so few out there. It gives helpful hints that are easily used.
As the author/guest editor makes quite clear, this is one of the topics that is neither an emphasized topic in the Veterinary educational process for today's little animal practitioner. Unless you are a Clinical or Surgical Oncologist in a hospital/hospice for homo sapiens, or have access to one when the time of need comes, as your dog ages, spend some time with this book. It is a amazing tutorial for the owner struggling with the need for such care and facing that brick wall of obsolescence in clinical veterinary medicine that has been taught to believe that the only form of palliative and/or hospice care for your canine is euthanasia. Far too a lot of canines and their benevolent owners are faced with such a recommendation because their Veterinarian has created the economic judgement for them, or the local system of Veterinary care is not adequately staffed to deal with the process of the continuation of life, even with certain limitations as to its quality, nor the help structure for the owner of that ailing pet. If you hear words such as "Its the humane thing to do", or "to place him/her 'out of their misery'", run, don't walk to an alternate source of end of life care. If you doubt this, first ask yourself, then ask your Veterinarian this question "Would you have your kid place to death by a physician if they presented in a human medical facility"?. There are a lot of alternatives to "Euthanasia" as indicated herein, so now ask this second question, "If Euthanasia is the "right thing to do" why do we always have to use Euphemisms such as "Put to sleep" when discussing it. There is a easy answer, who would wish to have their Veterinarian just "kill their pet with what they think is minimal pain and suffering, in a method related to what is used as "Capital Punishment" in humans just to that they, as owners, will not have to fulfill their commitment to its care throughout its lifetime.
I was expecting this book to have more info on becoming a data scientist. More on how to pull from SQL, and place into a language, or how to clean up a data set. Upon reading, I search that its more about buzz words for newcomers of the Computer Science field. Unless you just wish a dictionary to support explain the terms simply, I would not recommend the buy.
Simply a listing of skills necessary, not a how to book I was expecting from the title.
If you are looking into true dive into data science skip this book. You can google most of the information.
Lacking in specifics. Author throws lists of breezy generalizations at the page. Doesn't live up to the title. Proofreading very sloppy.
Neural networks and algorithms are described in an simple method with program examples, I'm learning python and working with neural networks, its a helpful resource for students.
This book is very practical and helpful. It includes the python pseudo code for a lot of primary Data Analysis From Scratch With Python, which was exactly what I was looking for. It would be helpful to have more info of what libraries commands come from. Recommend it .
Nice read! I genuinely trust there is a more noteworthy measure of such kind of book out there!good just in case you have to use the major e writer talked about here well ordered that exceptionally accommodating.
It is known from this book. I truly trust there is a greater amount of such sort of book out there!good just on the off possibility that you need to utilize the fundamental e author discussed here step by step that very helpful.
A very general and useful overview about data science. But not much more beyond this level. I think it is more like a collection of commonly used terms.
Wow, seriously. I just downloaded an AD. You CANNOT use it, not even to trial unless you subscribe, with payment info! I am not opposed to paying for amazing software, but NEVER when you use strategies like yours. All I can say is WOW!! Takes some *#!*!s.
Was ok for my son to learn his animals. My issue is 1 the falcon and eagle pictures don't match their names, 2 the star fish and eel has weird sounds (sounds like star battles sounds), when I didn't think they had sounds, 3 wood lice, tick, and worm even has a sound on this application when as far I Know they don't have a sound. I hope you fix the issue so children don't obtain confused on these animals
i left a review on 2018 saying your application is completly misleading and my review is deleted not only that you lied saying you fixed it when you didnt the star fish still makes darth vader sounds nice test trying to fool me
this is a amazing application to watch anime. I use to use the crunchyroll but I have to pay so I ended up uninstalling it. The only thing that is uneasy for this application is that there is no queue option. So basically, when you came back to continue watching a certain anime you'll have to hold going back and play it. There is no arrow to obtain through next episode for convenience.
This is the worst textbook I have ever read! It presents the material in a very complicated manner, hard to understand. Moreover, the language and the examples are so dry, it is hard to hold your eyes begin when reading the book. The issues in the end of each chapter are so unlike one another that one has to go to the internet to search related issues with solutions, and most issues are nothing like the examples presented in the chapters. Even for a person with extensive mathematical knowledge this book makes it impossible to learn the subject.