Damned Lies and Statistics: Untangling Numbers from the by Joel Best

By Joel Best

The following, by means of well known call for, is the updated edition to Joel Best's vintage advisor to knowing how numbers can confuse us. In his new afterword, top makes use of examples from fresh coverage debates to mirror at the demanding situations to bettering statistical literacy. considering that its book ten years in the past, Damned Lies and records has emerged because the go-to guide for recognizing undesirable information and studying to imagine severely approximately those influential numbers.

Joel most sensible is Professor of Sociology and felony Justice on the collage of Delaware. His many books contain Everyone's A Winner: lifestyles in Our Congratulatory tradition and Stat-Spotting: A box consultant to doubtful facts, either from UC Press.

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Extra info for Damned Lies and Statistics: Untangling Numbers from the Media, Politicians, and Activists (Updated Edition)

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Answer: Inferential statistics are used to make statements about a population, based upon information from a sample; they’re used to make inferences. Question: What is the difference between a statistic and a parameter, and how does this difference relate to the topic of inferential statistics? Answer: A statistic is a characteristic of a sample; a parameter is a characteristic of a population. Sample statistics are used to make inferences about population parameters. As you’ll soon discover, that’s where the hitch comes in.

In this example, the modal response would be Republican, because that was the Table 2-6 Identifying the Mode Scores/Values Scores/Values 1 2 2 7 9 9 9 21 1 2 2 7 7 7 9 9 9 25 29 9 is the mode Scores/Values 200 200 200 305 309 318 Bimodal modes = 7 and 9 Scores/Values 200 is the mode 20 22 28 30 36 38 No mode 28 CHAPTER 2 Describing Data and Distributions most frequent response. If nothing else, this provides a good example of a point I made earlier about levels of measurement: Which measure of central tendency you use is often a function of the level of measurement that’s involved.

Different samples are apt to yield different means. 16 CHAPTER 1 The What and How of Statistics We’ll eventually get to a more in-depth consideration of sampling error and how it operates to inhibit a direct leap from sample to population. First, though, let’s turn our attention to some of those summary measures that were mentioned earlier. For that, we’ll go to the next chapter. Chapter Summary Whether you realize it or not, you’ve done far more than just dip your toe into the waters of statistical analysis.

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