Posts with the tag « statistics » :

🔗 cart: home page

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This page contains computer software and documentation for creating density-equalizing maps or "cartograms" using the technique described in the paper Diffusion-based method for producing density equalizing maps, Michael T. Gastner and M. E. J. Newman, Proc. Natl. Acad. Sci. USA 101, 7499-7504 (2004).

🔗 Mathematics of War

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Quantitative analysis of conflict is a relatively new discipline that combines data collection, statistical analysis and modeling to understand war and inform political strategy. Our research group brings together an interdisciplinary group of physicists, mathematicians, computer scientists and political economists to use numbers and theoretical models to understand war.

🔗 Carl Heneghan: Why autism can't be diagnosed with brain scans | Science | guardian.co.uk

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How the brain scans results are portrayed is one of the simplest mistakes in interpreting diagnostic test accuracy to make. What has happened is, the sensitivity1 has been taken to be the positive predictive value2, which is what you want to know: if I have a positive test do I have the disease? Not, if I have the disease, do I have a positive test? It would help if the results included a measure called the likelihood ratio (LR), which is the likelihood that a given test result would be expected in a patient with the target disorder compared to the likelihood that the same result would be expected in a patient without that disorder. In this case the LR is 4.5. We've put up an article …

🔗 Discriminant Analysis

The main purpose of a discriminant function analysis is to predict group membership based on a linear combination of the interval variables. The procedure begins with a set of observations where both group membership and the values of the interval variables are known. The end result of the procedure is a model that allows prediction of group membership when only the interval variables are known.

🔗 The Regression-Discontinuity Design

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The regression-discontinuity design. What a terrible name! In everyday language both parts of the term have connotations that are primarily negative. To most people "regression" implies a reversion backwards or a return to some earlier, more primitive state while "discontinuity" suggests an unnatural jump or shift in what might otherwise be a smoother, more continuous process. To a research methodologist, however, the term regression-discontinuity (hereafter labeled "RD") carries no such negative meaning. Instead, the RD design is seen as a useful method for determining whether a program or treatment is effective.

🔗 GDP Fetishism

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Another marked change in most societies is an increase in inequality. This means that there is increasing disparity between average (mean) income and the median income (that of the “typical” person, whose income lies in the middle of the distribution of all incomes). If a few bankers get much richer, average income can go up, even as most individuals’ incomes are declining. So GDP per capita statistics may not reflect what is happening to most citizens.

🔗 Faulty Election Data – tehranbureau

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The best evidence for the validity of the arguments of the three opponents of the President for rejecting the results declared by the Interior Ministry is the data the Ministry itself has issued. In the chart below, compiled based on the data released by the Ministry and announced by Iran’s national television, a perfect linear relation between the votes received by the President and Mir Hossein Mousavi has been maintained, and the President’s vote is always half of the President’s. The vertical axis (y) shows Mr. Mousavi’s votes, and the horizontal (x) the President’s. R^2 shows the correlation coefficient: the closer it is to 1.0, the more perfect is the fit, and it is 0.9995, as close to 1.0 …

🔗 Survey Sampling Methods

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The advantage of probability sampling is that sampling error can be calculated. Sampling error is the degree to which a sample might differ from the population. When inferring to the population, results are reported plus or minus the sampling error. In nonprobability sampling, the degree to which the sample differs from the population remains unknown.