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11, 2005

All of It Ain't Necessarily So.

It has been awhile since I have blogged. I apologize. I have been sick and I have 8 classes and it is so hard to keep up on everything. For freshman and others reading this take my advice NEVER take 8 classes, even if it seems like it is the only was to graduate on time. So here is an entry on the whole of It Ain’t Necessarily So.

Prologue/Introduction/Chapter One:
Personally I liked this book. Many people had problems with it saying it was bias. I can understand that point but never the less I really enjoyed the book. These chapters were a good set up to what we were going to read these past 2-3 weeks. I liked in chapter one how they discussed “stories that aren’t covered”. This is a good point. Yes the book may be biased but isn’t this a good point? The media gives us the statistics that they want us to see. Thus some stories are not told.

Chapter 2 and 3:
“Readers ignorant of the operative definitions would have misinterpreted the results to make them seem worse than they really were; thus they would have been victimized by manipulation of the numbers” (58). I really like this quote. It really is true but people don’t even realize this. I admit I don’t even realize when I am manipulated by numbers. They give the example that poll questions are made to be answered one way or another and that can skew the numbers.

Chapter 4 and 5:
“It’s not that the same bit of data can be read in (at least) two ways” (86). I enjoyed chapter 5 a lot and their examples they use in chapter 5. Reading this book has really opened my mind to statistics and this chapter is a big reason. For example the statistics of the cases of diagnosed AIDS in women. The CDC only gave a percentage of women and not the raw data. If you actually look at the raw data you find that the raw data shows a different story about what the percentage seen in the news said. The raw data shows that the actually number of cases of women diagnosed went down, but also did the whole number of case men and women went down, because of this the percentage went up because the women’s decrease in raw data was not as much as the raw data of all the cases.

Chapter 6 and 7:
I blogged on this entry before on the day we did not have class.

Chapter 8 and 9:
“In other words, statistical information is inevitably one level removed from reality. We don’t learn directly about the subject of interest; instead we receive indirect information concerning reports about that subject”(134). I never realized this before when I was reading statistics in the news. It makes good sense though. They used the example that the rate of people reporting crimes has gone up but that doesn’t mean that crime has actually gone up. Yes the report is real but in a sense it is also like a half truth. I belief Kevin Hinton did his presentation and discussed half truths. I totally agree with him that at times we only get half truths.

Chapter 10 and Conclusion:
Like I stated earlier personally I enjoyed this book and I learned many things. Usually when I read statistics I don’t give them a second thought and I belief them. A lot of readers do this, but this book tries to separate the “good” facts vs. the “bad”. The book gave several great examples on how at times statistics are skewed. They can be skewed because the wording of the question is not good or because they give us a half truth. I never realized before that statistics weren’t at times a good measure of actual raw data but we are never given raw data. Many people did not like this book because they thought it was biased. I don’t think they were trying to be biased, when statistics are skewed they are skewed.

Posted by AshleyWelker at 11, 2005 08:44

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