How to lie with statistics summary chapter by chapter
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A mere glance offers an easy-to-read and accurate sense of things. People collecting and presenting the numbers to management could employ some of the tricks explained in this book and therefore, we should be careful when basing our decisions on those numbers. Yet it is often difficult to maintain the continual motivation needed to overcome the frequent obstacles and setbacks that litter the road to success. And something that I learned is that these errors are not always unintentional. Foolishly they require no meeting of canines or photos.

It has also been widely translated. The median average is most often used when there is a great range among the numbers being considered. And it is often more seriously misleading. Huff's book is more practical than theoretical. My only disappointment was in the lack of a chapter or discussion of how easy it is to create deliberately surveys that are skewed like the kind you might get from your elected representatives, in which three or four of the five possible answers are positive. By the time the data have been filtered through layers of statistical manipulation and reduced to a decimal-pointed average, the result begins to take on an aura of conviction that a closer look at the sampling would deny.

Sometimes a careful squint will sharpen the focus. And the median is, yes, 8 pounds. This project shows the readers to justify why the age of the car affects the price of the car. If your sample is large enough and selected properly, it will represent the whole well enough for most purposes. This course of basic statistic has provided me with the analytical skills to crunch numerical data and to make inference from it.

Response Bias: Tendency for people to over- or under-state the truth Non-response: People who complete surveys are systematically different from those who fail to respond. When you make a medical decision or assess the validity of a scientific study, we demand more proof. It is often more dangerous. Look sharply for unconscious bias. In this paper I will review types of statistical elements like: Descriptive, Inferential, hypothesis development and testing and the evaluation of the results.

In normal distributions, the three will be near each other, but in irregular distributions e. The reasons why Mr Kwok used this sampling method are that the cost per observation in the survey may be reduced and it also enables to increase the accuracy at a given cost. It is possibly more important to remember that any questionnaire is only a sample another level of the possible questions and that the answer the lady gives is no more than a sample third level of her attitudes and experiences on each question. The way out - always ask what is the kind of the average that someone is talking about. It says that these figures show that if you your son, your daughter attend college you will probably earn more money than if you decide to spend the next four years in some other manner.

Does the one publishing this result have anything to gain from the result? In the daze that follows the collision of statistics with the human mind, hardly anybody will notice the difference. Whether you avail yourself or not, this is another matter entirely. One of the biggest ideas shown in the book to my opinion was how he explained the power of the graph. Anything that is that specific might not be real. One of the trickiest ways to misrepresent statistical data is by means of a map.

So, when measuring the growth of, say the factory, increase the size of the factory image â€” and increase it across all the dimensions. When information is plotted on a graph, it can either be a true and clear show of the facts or a narrow enough slice of it to make a different point entirely. That is like refusing to read because writers sometimes use words to hide facts and relationships rather than to reveal them. Markus Zusak, the author of The Book Thief, realizes that humanity is more than a destructive force. For example, if you pack your clothes according to the average temperature for your vacation to Oklahoma City ignoring the ranges, you could end up in a hospital. Do the authors give you the standard error? If you have a barrel of beans, some red and some white, there is only one way to find out exactly how many of each color you have: Count 'em. For instance, the data collected would only be of one particular group of people, but they would claim it was the population.

Now in this case, is it that smoking was the cause of the bad grades or was it that the individuals who were getting bad grades decided to take up smoking? Unfortunately, some sources today commit the same oversight, perhaps more concerned about Kinsey's influence than his accuracy. In fact, when A and B happen together, we can't necessarily know whether A causes B or whether it was the other way around. It's the kind of book that doesn't need a lot of outside instruction. You go from door to door by day - and miss most of the employed people. No matter how loud I shout: A year in the life of juvenile court. This book is not an academic textbook, or a workbook, but each chapter is discrete so that it could stand alone, and the subject matter easily lends itself to sample problems. It gives the readers the knowledge necessary to intelligently question and understand the story behind the numbers.

Written by a non-statistician in hokey language and illustrated by humorous line drawings, is as relevant and enjoyable as when it first appeared in 1954. Five years later it was 105 million. First and foremost, ask yourself the right questions. Statistics can lie in many ways the first way is by using a sample that has a bias. An unwarranted assumption is being made that since smoking and low grades go together, smoking causes low grades. With equal validity you can describe it as a one hundred percent increase. The data will be presented as the average, but the type of average that is taken is not given.