Confidence intervals - CSI Math Department
... It is claimed that the assumption of a normally distributed population can be relaxed, as long as the parent distribution is not too skewed. That is, the assumptions are robust to small differences in the population. You can verify this by checking if the number of CIs that miss is dramatically diff ...
... It is claimed that the assumption of a normally distributed population can be relaxed, as long as the parent distribution is not too skewed. That is, the assumptions are robust to small differences in the population. You can verify this by checking if the number of CIs that miss is dramatically diff ...
Estimating and Simulating a Model for Mean Reversion (in format)
... random numbers uniformly distributed between 0 and 1. These numbers can be converted to numbers that are normally distributed with mean zero and standard deviations one by using the function NORMSINV. If RAND( ) is uniformly distributed between 0 and 1, then NORMSINV(RAND( )) is normally distributed ...
... random numbers uniformly distributed between 0 and 1. These numbers can be converted to numbers that are normally distributed with mean zero and standard deviations one by using the function NORMSINV. If RAND( ) is uniformly distributed between 0 and 1, then NORMSINV(RAND( )) is normally distributed ...
Determine which of the four levels of measurement
... work full time in samples of size 16. 52) According to a college survey, 22% of all students work full time. Find the standard deviation for the number of students who work full time in samples of size 16. Determine if the outcome is unusual. Consider as unusual any result that differs from the mean ...
... work full time in samples of size 16. 52) According to a college survey, 22% of all students work full time. Find the standard deviation for the number of students who work full time in samples of size 16. Determine if the outcome is unusual. Consider as unusual any result that differs from the mean ...
1 Introduction
... One interesting application I came upon in a course on Microarray analysis is the genomic software application EASE (Expression Analysis Systematic Explorer).6 In experiments and analyses that use gene expression data, researchers often finalize their study with an annotated list of genes found to b ...
... One interesting application I came upon in a course on Microarray analysis is the genomic software application EASE (Expression Analysis Systematic Explorer).6 In experiments and analyses that use gene expression data, researchers often finalize their study with an annotated list of genes found to b ...
German tank problem
In the statistical theory of estimation, the problem of estimating the maximum of a discrete uniform distribution from sampling without replacement is known in English as the German tank problem, due to its application in World War II to the estimation of the number of German tanks.The analyses illustrate the difference between frequentist inference and Bayesian inference.Estimating the population maximum based on a single sample yields divergent results, while the estimation based on multiple samples is an instructive practical estimation question whose answer is simple but not obvious.