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The use of a sequence of experiments, where the design of each may depend on the results of previous experiments, including the possible decision to stop experimenting, is within the scope of sequential analysis, a field that was pioneered [12] by Abraham Wald in the context of sequential tests of statistical hypotheses. [13]
Particle size analysis, particle size measurement, or simply particle sizing, is the collective name of the technical procedures, or laboratory techniques which determines the size range, and/or the average, or mean size of the particles in a powder or liquid sample.
Essentially, the mean is the location of the PDF on the real number line, and the variance is a description of the scatter or dispersion or width of the PDF. To illustrate, Figure 1 shows the so-called Normal PDF , which will be assumed to be the distribution of the observed time periods in the pendulum experiment.
Design and Analysis of Experiments. Handbook of Statistics. pp. 1149–1199. Majumdar, D. "Optimal and Efficient Treatment-Control Designs". Design and Analysis of Experiments. Handbook of Statistics. pp. 1007–1054. Stufken, J. "Optimal Crossover Designs". Design and Analysis of Experiments. Handbook of Statistics. pp. 63–90.
The Mann–Whitney test (also called the Mann–Whitney–Wilcoxon (MWW/MWU), Wilcoxon rank-sum test, or Wilcoxon–Mann–Whitney test) is a nonparametric statistical test of the null hypothesis that, for randomly selected values X and Y from two populations, the probability of X being greater than Y is equal to the probability of Y being greater than X.
The sample size is an important feature of any empirical study in which the goal is to make inferences about a population from a sample. In practice, the sample size used in a study is usually determined based on the cost, time, or convenience of collecting the data, and the need for it to offer sufficient statistical power. In complex studies ...
A scientific control is an experiment or observation designed to minimize the effects of variables other than the independent variable (i.e. confounding variables). [1] This increases the reliability of the results, often through a comparison between control measurements and the other measurements.
The literature on the analysis of capture-recapture studies has blossomed since the early 1990s [citation needed]. There are very elaborate statistical models available for the analysis of these experiments. [15] A simple model which easily accommodates the three source, or the three visit study, is to fit a Poisson regression model.
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