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Poisson and Normal Distributions [PDF]
, 1974 The Poisson distribution is of great importance in theory and in practice. It has the added virtue of being a simple mathematical object. We could have introduced it at an earlier stage in the book, and the reader was alerted to this in §4.4. However, the belated entrance will give it more prominence, as well as a more thorough discussion than would be
Kai Lai Chung, Farid AitSahlia
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2011
This chapter examines some important properties of the normal distribution. We also see how the fact that data follow a normal distribution can actually be verified. Finally, we see how to estimate the statistical uncertainty of a sample average.
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This chapter examines some important properties of the normal distribution. We also see how the fact that data follow a normal distribution can actually be verified. Finally, we see how to estimate the statistical uncertainty of a sample average.
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1989
You should recall that one view of the binomial distribution is as an approximation to the hypergeomtric; also, for “large” n and “small” p, the binomial can be approximated by the Poisson. Here we introduce a third approximation for the binomial in terms of “large” n and “moderate” p using the so-called normal density $${e^{{ - \frac{2}{2 ...
Gerald S. Rogers, Hung T. Nguyen
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You should recall that one view of the binomial distribution is as an approximation to the hypergeomtric; also, for “large” n and “small” p, the binomial can be approximated by the Poisson. Here we introduce a third approximation for the binomial in terms of “large” n and “moderate” p using the so-called normal density $${e^{{ - \frac{2}{2 ...
Gerald S. Rogers, Hung T. Nguyen
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2021
When the number of trials increases in the discrete distributions illustrated in the previous chapters, the probability mass distribution tends to become symmetric around a central value. For large enough numbers, the shape of these distributions is not far from what we observe in many experimental data distributions.
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When the number of trials increases in the discrete distributions illustrated in the previous chapters, the probability mass distribution tends to become symmetric around a central value. For large enough numbers, the shape of these distributions is not far from what we observe in many experimental data distributions.
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2009
The normal and t distributions are heavily used in statistical analysis. The normal and t-tables on the Rcmdr menu can be used to look up probabilities p given quantiles (z- or t-values), or quantiles (z or t) corresponding to known p-values. Some of these probability functions are also available in Excel (as part of the Analysis toolpack), but the R ...
Erich Neuwirth, Richard M. Heiberger
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The normal and t distributions are heavily used in statistical analysis. The normal and t-tables on the Rcmdr menu can be used to look up probabilities p given quantiles (z- or t-values), or quantiles (z or t) corresponding to known p-values. Some of these probability functions are also available in Excel (as part of the Analysis toolpack), but the R ...
Erich Neuwirth, Richard M. Heiberger
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1981
This chapter discusses the normal distribution. There are a great number of continuous distributions. The normal distribution is undoubtedly the one that is the most widely used in applications of statistics. A normal distribution is completely specified by two parameters, the theoretical mean and the theoretical variance of the population.
Patrick Murphy, H.T. Hayslett
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This chapter discusses the normal distribution. There are a great number of continuous distributions. The normal distribution is undoubtedly the one that is the most widely used in applications of statistics. A normal distribution is completely specified by two parameters, the theoretical mean and the theoretical variance of the population.
Patrick Murphy, H.T. Hayslett
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Modeling piezocone cone penetration (CPTU) parameters of clays as a multivariate normal distribution
, 2014This study examines the possibility of modeling piezocone cone penetration (CPTU) cone tip resistance, excessive pore pressure behind the cone, undrained shear strength, and overconsolidation ratio of lightly overconsolidated clays as a multivariate ...
ChingJianye +2 more
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Handbook of the Normal Distribution
Technometrics, 1982Genesis: an historical background basic properties expansions and algorithms characterizations sampling distributions limit theorems and expansions normal approximations to distributions order statistics from normal samples the bivariate normal distribution bivariate normal sampling distributions point estimation statistical intervals.
C. B. Read, Jagdish K. Patel
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2004
The book reviews the state-of-the-art advances in skew-elliptical distributions and provides many new developments in a single volume, collecting theoretical results and applications previously scattered throughout the literature. The main goal of this research area is to develop flexible parametric classes of distributions beyond the classical normal ...
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The book reviews the state-of-the-art advances in skew-elliptical distributions and provides many new developments in a single volume, collecting theoretical results and applications previously scattered throughout the literature. The main goal of this research area is to develop flexible parametric classes of distributions beyond the classical normal ...
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