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Titlebook: Statistical Analysis of Clinical Data on a Pocket Calculator, Part 2; Statistics on a Pock Ton J. Cleophas,Aeilko H. Zwinderman Book 2012 T

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Fuzzy Modeling for Imprecise and Incomplete Data,partly “yes” and “no” at the same time. It can be used to match any type of data, particularly incomplete and imprecise data, and it is able to improve precision of such data. It can be applied with any type of statistical distribution and it is, particularly, suitable for uncommon and unexpected no
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Goodness of Fit Tests for Normal and Cumulatively Normal Data,to be sensitive for testing the data. Data files that lack goodness of fit can be analyzed using distribution free methods, like Monte Carlo modeling and neural network modeling (SPSS for Starters, Part 2 from the same authors, Springer New York, 2012).
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Superiority Testing Instead of Null Hypothesis Testing,tudy means testing whether the study meets its a priori defined expected power. Many therapeutic studies may be able to reject their null hypotheses, and, are, thus, statistically significant, but they do not meet their expected power. Although p-values are widely reported, power is rarely given in
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,Variability Analysis With the Bartlett’s Test,gans, variability of drug concentrations is important, as in some cases too little and in other cases dangerously high levels get through. Also, variabilities in drug response may be important. For example, the spread of glucose levels of a slow-release-insulin is important. In part 1 of this title,
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Meta-Analysis of Continuous Data,he overall results a weighted average has to be calculated. Heterogeneity in a meta-analysis means that the differences in the results between the studies are larger than could happen by chance. The calculation of the overall result and the test for heterogeneity is demonstrated underneath.
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Assessing Manipulated Data,8 as final digits were virtually unobserved. We will test whether the observed frequencies of the final digits are compatible with equal frequencies, as expected, and we will use a Chi-square test for that purpose.
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