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STATISTICAL TESTS OF THE LOGNORMAL DISTRIBUTION AS A
STATISTICAL TESTS OF THE LOGNORMAL DISTRIBUTION AS A

... January 1990 forward. The three-month and the six-month discount rates were converted to a quarterly nominal rate for the three-month security and a bond-equivalent yield for the six-month security by application of the formula given in [5, p. 178] with the appropriate number of days until maturity. ...
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... interval from a to b, denoted by P (a ≤ X ≤ b), is equal to the area under the density curve over the interval from a to b on the x–axis. Areas of this sort based on the density curve give the probabilities which a single value of X, chosen at random from the infinite population of possible values o ...
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Exercises 1. Descriptive Statistics 2. Probability and Expected Value

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Quantile Function for Rayleigh Distribution Kapasitans-Voltaj (C

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Sampling Distributions - Associate Professor Leigh Blizzard

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... expense even if we are convinced that the difference is real. These sorts of practical decisions are ultimately up to us, statistics gives an objective assessment of the available evidence which we can use to make rational decisions. The above discussion has introduced some important statistical co ...
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... standard deviation.  The more the data are concentrated, the smaller the range, interquartile range, variance, and standard deviation.  If the values are all the same (no variation), all these measures will be zero.  None of these measures are ever negative. Statistics for Managers Using Microsof ...
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Foundations of statistics

Foundations of statistics is the usual name for the epistemological debate in statistics over how one should conduct inductive inference from data. Among the issues considered in statistical inference are the question of Bayesian inference versus frequentist inference, the distinction between Fisher's ""significance testing"" and Neyman-Pearson ""hypothesis testing"", and whether the likelihood principle should be followed. Some of these issues have been debated for up to 200 years without resolution.Bandyopadhyay & Forster describe four statistical paradigms: ""(1) classical statistics or error statistics, (ii) Bayesian statistics, (iii) likelihood-based statistics, and (iv) the Akaikean-Information Criterion-based statistics"".Savage's text Foundations of Statistics has been cited over 10000 times on Google Scholar. It tells the following.It is unanimously agreed that statistics depends somehow on probability. But, as to what probability is and how it is connected with statistics, there has seldom been such complete disagreement and breakdown of communication since the Tower of Babel. Doubtless, much of the disagreement is merely terminological and would disappear under sufficiently sharp analysis.
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