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Probit analysis is the technique most commonly employed in the bioassay, specifically toxicological experiments where the group of animals is subjected to known levels of a toxin and a model is needed to relate the proportion surviving at the particular dose, to the dose. In this kind of evaluation the probit transformation of a proportion is modeled as a linear function of the dose or more frequently, the logarithm of the dose. Estimates of the parameters in the model are found by the maximum likelihood estimation.
Bioinformatics : Essentially the application of the information theory to biology to deal with the deluge of the information resulting from the advances in molecular biology. The m
The biggest and smallest variate values among the sample of observations. Significant in various regions, for instance flood levels of the river, speed of wind and snowfall.
we are testing : Ho: µ=40 versus Ha: µ>40 (a= 0.01) Suppose that the test statistic is z0=2.75 based on a sample size of n=25. Assume that data are normal with mean mu and standa
methods of measuring trend
Zero-inflated Poisson regression is the model for count data with the excess zeros. It supposes that with probability p the only possible observation is 0 and with the probabilit
facts and statistics about daycare
Hello! I am currently in graduate school earning a masters in mental health counseling. I am in a stats course at current and we are reviewing z-scores. I am a little lost because
meaning,uses,shortcomings and drawbacks of vital statistics
The model which is applicable to the longitudinal data in which the dropout process might give rise to the informative lost values. Specifically if the study protocol specifies the
Healthy worker effect : The occurrence whereby employed individuals tend to have lower mortality rates than those who are unemployed. The effect, which can pose the serious problem
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