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Impressões e sentimentos de gestantes em relação à ultra-sonografia obstétrica no contexto de normalidade fetal; Impressions and feelings of pregnant women concerning obstetric ultrasound in the context of fetal normality

Gomes, Aline Grill; Piccinini, Cesar Augusto
Fonte: Universidade Federal do Rio Grande do Sul Publicador: Universidade Federal do Rio Grande do Sul
Tipo: Artigo de Revista Científica Formato: application/pdf
Português
Relevância na Pesquisa
36.76%
O objetivo desta pesquisa foi investigar as impressões e sentimentos das gestantes sobre a ultra-sonografia obstétrica, no contexto de normalidade fetal. Participaram do estudo 11 gestantes primíparas, com idades entre 18 e 35 anos e idades gestacional entre 11 e 24 semanas, que estavam sendo submetidas pela primeira vez à ultrasonografia. Elas responderam a uma entrevista semi-estruturada, antes, logo depois e três semanas depois do exame. Análise de conteúdo qualitativa das entrevistas revelou a satisfação e a intensidade vivenciadas no exame; a sua importância ao permitir conhecer o bebê antes do nascimento; por promover um sentimento de concretização da gravidez e do bebê; e, por informar sobre a saúde do bebê, possibilitando intervenções precoces. Repercussões do exame envolveram, ainda, maior aproximação e cuidado dos familiares para com a gestante. A ultra-sonografia parece ser um momento notório no transcorrer da gravidez, merecendo atenção dos familiares e, especialmente, dos profissionais de saúde envolvidos.; The aim of this study was to investigate the impressions and feelings of pregnant women concerning obstetric ultrasound in the context of fetal normality. Eleven primiparous pregnant women, ages 18 to 35 and with 11 to 24 weeks of gestation...

An empirical power comparison of univariate goodness-of-fit tests for normality

Xavier Romão; Raimundo Delgado; Aníbal Costa
Fonte: Universidade do Porto Publicador: Universidade do Porto
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
27.1%
A comprehensive power comparison study of existing tests for normality is proposed. Given the importance of this subject and the widespread development of normality tests, comprehensive descriptions and power comparisons of such tests are of considerable interest. Since recent comparison studies do not include several interesting and more recently developed tests, a further comparison of normality tests is considered to be of foremost interest. The study addresses the performance of 33 normality tests, for various sample sizes, considering several significance levels and for a number of symmetric, asymmetric and modified normal distributions. General recommendations for normality testing resulting from the study are defined according to the nature of the non-normality.

Excess returns and normality

Boavida, João Pedro do Carmo
Fonte: Instituto Superior de Economia e Gestão Publicador: Instituto Superior de Economia e Gestão
Tipo: Dissertação de Mestrado
Publicado em /06/2011 Português
Relevância na Pesquisa
36.98%
Mestrado em Economia Monetária e Financeira; In this dissertation, I assess under which circumstances normality can be a good descriptive model for the U.S. excess returns. I explore two possible sources of deviations from normal¬ity: structural breaks and regime switching in long term aggregate time series. In addition, I study temporal aggregation (i.e., considering the frequency of data as a variable) for ex¬cess returns in short term time series. My main findings are summarized as follows. First, using long spanning monthly time series data from 1871 to 2010, I find that (1) there are structural breaks in monthly excess returns between pre-WWII and post-WWII data; and, (2) while pre-WWII data is consistent with normality, post-WWII data is not. Second, I provide evidence of two market regimes for excess returns in post-WWII data. These regimes may be seen as bull and bear market conditions. Third, using high frequency post-WWII data, I check for aggregational Gaussianity, from daily to annual data. I find that Gaus-sianity depends on the frequency of data: it may hold for highly aggregate data (starting from semi-annual to annual data) but it does not hold for high frequency data (less than semi-annual). My main contribution is to demonstrate the "normality survival" when fre¬quency is taken as a variable. After a careful look at the available literature on aggregational Gaussianity...

Large standard deviations and logarithmic-normality: The truth about hemocyte counts in Drosophila

Sorrentino, Richard Paul
Fonte: Landes Bioscience Publicador: Landes Bioscience
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
27.05%
While many quantifiable biological phenomena can be described by making use of an assumption of normality in the distribution of individual values, many biological phenomena are not accurately described by the normal distribution. An unquestioned assumption of normality of distribution of possible outcomes can lead to misinterpretation of data, which could have serious consequences. Thus it is extremely important to test the validity of an assumption of normality of possible outcomes. As it turns out, the logarithmic-normal (log-normal) distribution pattern is often far more accurate in describing statistical biological phenomena. Herein I examine large samples of values for circulating blood cell (hemocyte) concentration (CHC) among both wild-type and mutant Drosophila larvae, and demonstrate in both cases that the distribution of individual values does not conform to normality, but does conform to log-normality.

Reference values and the problem of health as normality: a veterinary attempt in the light of a one health approach

Lerner, Henrik; Berzell, Martin
Fonte: Co-Action Publishing Publicador: Co-Action Publishing
Tipo: Artigo de Revista Científica
Publicado em 10/09/2014 Português
Relevância na Pesquisa
26.98%
Reference values seem crucial to both veterinary medicine and human medicine. The main critique is that the theoretical connections between the concepts of reference values, normality, and health are weak. In this paper, we analyze especially one attempt in veterinary medicine to establish such a theoretical connection. We find that this attempt fails because it is circular. In conclusion, we would postulate that there are two apparent ways forward: to aim for a definition of health not based on the concept of normality, or to develop the concept of normality as separate from statistical normality. These goals can be reached with a one health perspective.

Testing Normality : A GMM Approach

BONTEMPS, Christian; MEDDAHI, Nour
Fonte: Université de Montréal Publicador: Université de Montréal
Tipo: Artigo de Revista Científica Formato: 555479 bytes; application/pdf
Português
Relevância na Pesquisa
36.76%
In this paper, we consider testing marginal normal distributional assumptions. More precisely, we propose tests based on moment conditions implied by normality. These moment conditions are known as the Stein (1972) equations. They coincide with the first class of moment conditions derived by Hansen and Scheinkman (1995) when the random variable of interest is a scalar diffusion. Among other examples, Stein equation implies that the mean of Hermite polynomials is zero. The GMM approach we adopted is well suited for two reasons. It allows us to study in detail the parameter uncertainty problem, i.e., when the tests depend on unknown parameters that have to be estimated. In particular, we characterize the moment conditions that are robust against parameter uncertainty and show that Hermite polynomials are special examples. This is the main contribution of the paper. The second reason for using GMM is that our tests are also valid for time series. In this case, we adopt a Heteroskedastic-Autocorrelation-Consistent approach to estimate the weighting matrix when the dependence of the data is unspecified. We also make a theoretical comparison of our tests with Jarque and Bera (1980) and OPG regression tests of Davidson and MacKinnon (1993). Finite sample properties of our tests are derived through a comprehensive Monte Carlo study. Finally...

An Alternative Goodness-of-fit Test for Normality with Unknown Parameters

Shi, Weiling
Fonte: FIU Digital Commons Publicador: FIU Digital Commons
Tipo: Artigo de Revista Científica Formato: application/pdf
Português
Relevância na Pesquisa
36.76%
Goodness-of-fit tests have been studied by many researchers. Among them, an alternative statistical test for uniformity was proposed by Chen and Ye (2009). The test was used by Xiong (2010) to test normality for the case that both location parameter and scale parameter of the normal distribution are known. The purpose of the present thesis is to extend the result to the case that the parameters are unknown. A table for the critical values of the test statistic is obtained using Monte Carlo simulation. The performance of the proposed test is compared with the Shapiro-Wilk test and the Kolmogorov-Smirnov test. Monte-Carlo simulation results show that proposed test performs better than the Kolmogorov-Smirnov test in many cases. The Shapiro Wilk test is still the most powerful test although in some cases the test proposed in the present research performs better.

An Assessment of the Performances of Several Univariate Tests of Normality

Adefisoye, James Olusegun
Fonte: FIU Digital Commons Publicador: FIU Digital Commons
Tipo: Artigo de Revista Científica Formato: application/pdf
Português
Relevância na Pesquisa
36.76%
The importance of checking the normality assumption in most statistical procedures especially parametric tests cannot be over emphasized as the validity of the inferences drawn from such procedures usually depend on the validity of this assumption. Numerous methods have been proposed by different authors over the years, some popular and frequently used, others, not so much. This study addresses the performance of eighteen of the available tests for different sample sizes, significance levels, and for a number of symmetric and asymmetric distributions by conducting a Monte-Carlo simulation. The results showed that considerable power is not achieved for symmetric distributions when sample size is less than one hundred and for such distributions, the kurtosis test is most powerful provided the distribution is leptokurtic or platykurtic. The Shapiro-Wilk test remains the most powerful test for asymmetric distributions. We conclude that different tests are suitable under different characteristics of alternative distributions.

Normality tests for spatialy correlated data

Pardo-Iguzquiza, E.; Dowd, P.
Fonte: Kluwer Academic/Plenum Publ Publicador: Kluwer Academic/Plenum Publ
Tipo: Artigo de Revista Científica
Publicado em //2004 Português
Relevância na Pesquisa
27.05%
In studies that involve a finite sample size of spatial data it is often of interest to test (statistically) the assumption that the marginal (or univariate) distribution of the data is Gaussian (normal). This may be important per se because, for example, a data transformation may be desired if the normality hypothesis is rejected, or it may provide a way of testing other hypotheses, such as lognormality, by testing the normality of the logarithms of the observations. The most commonly used tests, such as the Kolmogorov–Smirnov (K–S), chi-square (χ2), and Shapiro–Wilks (S–W) tests, are designed on the assumption that the observations are independent and identically distributed (iid). In geostatistical applications, however, this is not usually the case unless the spatial covariance (semivariogram) function is a pure nugget variance. If the covariance structure has a (practical) range greater than the minimum distance between observations, the data are correlated and the standard tests cannot be applied to the probability density function (pdf) or cumulative probability function (cdf) estimated directly from the data. The problem with correlated data arises not from the correlation per se but from cases in which correlated data are clustered rather than being located on a regular grid. In these cases inferences requiring iid assumptions may be seriously biased because of the spatial correlation among the observations. If unbiased (i.e....

A power comparison of various tests of univariate normality on Ex-Gaussian distributions

Marmolejo Ramos, F.; Gonzalez-Burgos, J.
Fonte: Hogrefe Publishing Publicador: Hogrefe Publishing
Tipo: Artigo de Revista Científica
Publicado em //2013 Português
Relevância na Pesquisa
36.89%
A power analysis of seven normality tests against the Ex-Gaussian distribution (EGd) is presented. The EGd is selected on the basis that it is a particularly well-suited distribution to accommodate positively skewed distributions such as those observed in reaction times data. A pre-assessment of the power of the selected tests across various types of distributions was done via a meta-analysis and a comparison with other power analyses reported in the literature was also performed. General recommendations are given as to which tests should be used to test normality in data suspected to resemble an EG distribution. Additionally, some topics for future research regarding the use of confidence intervals and the computation of accurate critical values are outlined.; Fernando Marmolejo-Ramos, Jorge González-Burgos

Univariate Analysis and Normality Test Using SAS, Stata, and SPSS

Park, Hun Myoung
Fonte: Universidade de Indiana Publicador: Universidade de Indiana
Português
Relevância na Pesquisa
37.1%
Descriptive statistics provide important information about variables to be analyzed. Mean, median, and mode measure central tendency of a variable. Measures of dispersion include variance, standard deviation, range, and interquantile range (IQR). Researchers may draw a histogram, stem-and-leaf plot, or box plot to see how a variable is distributed. Statistical methods are based on various underlying assumptions. One common assumption is that a random variable is normally distributed. In many statistical analyses, normality is often conveniently assumed without any empirical evidence or test. But normality is critical in many statistical methods. When this assumption is violated, interpretation and inference may not be reliable or valid. The t-test and ANOVA (Analysis of Variance) compare group means, assuming a variable of interest follows a normal probability distribution. Otherwise, these methods do not make much sense. Figure 1 illustrates the standard normal probability distribution and a bimodal distribution. How can you compare means of these two random variables? There are two ways of testing normality (Table 1). Graphical methods visualize the distributions of random variables or differences between an empirical distribution and a theoretical distribution (e.g....

A New method for Testing Normality based upon a Characterization of the Normal Distribution

Melbourne, Davayne A
Fonte: FIU Digital Commons Publicador: FIU Digital Commons
Tipo: Artigo de Revista Científica Formato: application/pdf
Português
Relevância na Pesquisa
37.17%
The purposes of the thesis were to review some of the existing methods for testing normality and to investigate the use of generated data combined with observed to test for normality. The approach to testing for normality is in contrast to the existing methods which are derived from observed data only. The test of normality proposed follows a characterization theorem by Bernstein (1941) and uses a test statistic D*, which is the average of the Hoeffding’s D-Statistic between linear combinations of the observed and generated data to test for normality. Overall, the proposed method showed considerable potential and achieved adequate power for many of the alternative distributions investigated. The simulation results revealed that the power of the test was comparable to some of the most commonly used methods of testing for normality. The test is performed with the use of a computer-based statistical package and in general takes a longer time to run than some of the existing methods of testing for normality.

Testing Mean-Variance Efficiency in CAPM with Possibly Non-Gaussian Errors : An Exact Simulation-Based Approach

BEAULIEU, Marie-Claude; DUFOUR, Jean-Marie; KHALAF, Lynda
Fonte: Université de Montréal Publicador: Université de Montréal
Tipo: Artigo de Revista Científica Formato: 400691 bytes; application/pdf
Português
Relevância na Pesquisa
26.98%
In this paper we propose exact likelihood-based mean-variance efficiency tests of the market portfolio in the context of Capital Asset Pricing Model (CAPM), allowing for a wide class of error distributions which include normality as a special case. These tests are developed in the frame-work of multivariate linear regressions (MLR). It is well known however that despite their simple statistical structure, standard asymptotically justified MLR-based tests are unreliable. In financial econometrics, exact tests have been proposed for a few specific hypotheses [Jobson and Korkie (Journal of Financial Economics, 1982), MacKinlay (Journal of Financial Economics, 1987), Gib-bons, Ross and Shanken (Econometrica, 1989), Zhou (Journal of Finance 1993)], most of which depend on normality. For the gaussian model, our tests correspond to Gibbons, Ross and Shanken’s mean-variance efficiency tests. In non-gaussian contexts, we reconsider mean-variance efficiency tests allowing for multivariate Student-t and gaussian mixture errors. Our framework allows to cast more evidence on whether the normality assumption is too restrictive when testing the CAPM. We also propose exact multivariate diagnostic checks (including tests for multivariate GARCH and mul-tivariate generalization of the well known variance ratio tests) and goodness of fit tests as well as a set estimate for the intervening nuisance parameters. Our results [over five-year subperiods] show the following: (i) multivariate normality is rejected in most subperiods...

The Concept of Harm and the Significance of Normality

Kahane, Guy; Savulescu, Julian
Fonte: Blackwell Publishing Ltd Publicador: Blackwell Publishing Ltd
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
27.05%
Many believe that severe intellectual impairment, blindness or dying young amount to serious harm and disadvantage. It is also increasingly denied that it matters, from a moral point of view, whether something is biologically normal to humans. We show that these two claims are in serious tension. It is hard explain how, if we do not ascribe some deep moral significance to human nature or biological normality, we could distinguish severe intellectual impairment or blindness from the vast list of seemingly innocent ways in which we fail to have as much wellbeing as we could, such not having super-intelligence, or not living to 130. We consider a range of attempts to draw this intuitive normative distinction without appealing to normality. These, we argue, all fail. But this doesn't mean that we cannot draw this distinction or that we must, implausibly, conclude that biological normality does possess an inherent moral importance. We argue that, despite appearances, it is not biological normality but rather statistical normality that, although lacking any intrinsic moral significance, nevertheless makes an important moral difference in ways that explain and largely justify the intuitive distinction.

Normality preserving operations for Cantor series expansions and associated fractals part I

Airey, Dylan; Mance, Bill
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
27.05%
It is well known that rational multiplication preserves normality in base $b$. We study related normality preserving operations for the $Q$-Cantor series expansions. In particular, we show that while integer multiplication preserves $Q$-distribution normality, it fails to preserve $Q$-normality in a particularly strong manner. We also show that $Q$-distribution normality is not preserved by non-integer rational multiplication on a set of zero measure and full Hausdorff dimension.; Comment: 10 pages

Cantor Series Constructions Contrasting Two Notions of Normality

Altomare, Christian; Mance, Bill
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Português
Relevância na Pesquisa
27.1%
A. R\'enyi \cite{Renyi} made a definition that gives a generalization of simple normality in the context of $Q$-Cantor series. In \cite{Mance}, a definition of $Q$-normality was given that generalizes the notion of normality in the context of $Q$-Cantor series. In this work, we examine both $Q$-normality and $Q$-distribution normality, treated in \cite{Laffer} and \cite{Salat}. Specifically, while the non-equivalence of these two notions is implicit in \cite{Laffer}, in this paper, we give an explicit construction witnessing the nontrivial direction. That is, we construct a base $Q$ as well as a real $x$ that is $Q$-normal yet not $Q$-distribution normal. We next approach the topic of simultaneous normality by constructing an explicit example of a base $Q$ as well as a real $x$ that is both $Q$-normal and $Q$-distribution normal.

Normal numbers and normality measure

Aistleitner, Christoph
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 07/02/2013 Português
Relevância na Pesquisa
26.98%
The normality measure $\mathcal{N}$ has been introduced by Mauduit and S{\'a}rk{\"o}zy in order to describe the pseudorandomness properties of finite binary sequences. Alon, Kohayakawa, Mauduit, Moreira and R{\"o}dl proved that the minimal possible value of the normality measure of an $N$-element binary sequence satisfies $$ (1/2 + o(1)) \log_2 N \leq \min_{E_N \in \{0,1\}^N} \mathcal{N}(E_N) \leq 3 N^{1/3} (\log N)^{2/3} $$ for sufficiently large $N$. In the present paper we improve the upper bound to $c (\log N)^2$ for some constant $c$, by this means solving the problem of the asymptotic order of the minimal value of the normality measure up to a logarithmic factor, and disproving a conjecture of Alon \emph{et al.}. The proof is based on relating the normality measure of binary sequences to the discrepancy of normal numbers in base 2.

Multivariate Non-Normality in the WMAP 1st Year Data

Dineen, Patrick; Coles, Peter
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 29/11/2005 Português
Relevância na Pesquisa
26.98%
The extraction of cosmological parameters from microwave background observations relies on specific assumptions about the statistical properties of the data, in particular that the p-point distributions of temperature fluctuations are jointly-normal. Using a battery of statistical tests, we assess the multivariate Gaussian nature of the Wilkinson Microwave Anisotropy Probe (WMAP) 1st year data. The statistics we use fall into three classes which test different aspects of joint-normality: the first set assess the normality of marginal (one-point) distributions using familiar univariate methods; the second involves statistics that directly assess joint-normality; and the third explores the evidence of non-linearity in the relationship between variates. We applied these tests to frequency maps, `foreground-cleaned' assembly maps and all-sky CMB-only maps. The assembly maps are of particular interest as when combined with the kp2 mask, we recreate the region used in the computation of the angular power spectrum. Significant departures from normality were found in all the maps. In particular, the kurtosis coefficient, D'Agostino's statistic and bivariate kurtosis calculated from temperature pairs extracted from all the assembly maps were found to be non-normal at 99% confidence level. We found that the results were unaffected by the size of the Galactic cut and were evident on either hemisphere of the CMB sky. The latter suggests that the non-Gaussianity is not simply related to previous claims of north-south asymmetry or localized abnormalities detected through wavelet techniques.; Comment: 15 pages...

On the solutions of weak normality equations in multidimensional case

Sharipov, Ruslan
Fonte: Universidade Cornell Publicador: Universidade Cornell
Tipo: Artigo de Revista Científica
Publicado em 14/12/2000 Português
Relevância na Pesquisa
26.98%
The system of weak normality equations constitutes a part in the complete system of normality equations. Solutions of each of these two systems of equations are associated with some definite classes of Newtonian dynamical systems in Riemannian manifolds. In this paper for the case of simplest flat Riemannian manifold $M=\Bbb R^n$ with $n\geq 3$ we show that there exist solutions of weak normality equations that do not solve complete system of normality equations in whole. Hence associated classes of Newtonian dynamical systems do not coincide with each other.; Comment: AmSTeX, 16 pages, amsppt style

Applicability of attenuation relations for regional studies

Joshi,Anand; Kumar,Ashvini; Lomnitz,Cinna; Castaños,Heriberta; Akhtar,Shahid
Fonte: Instituto de Geofísica, UNAM Publicador: Instituto de Geofísica, UNAM
Tipo: Artigo de Revista Científica Formato: text/html
Publicado em 01/12/2012 Português
Relevância na Pesquisa
26.98%
This paper discusses the applicability of different ground motion prediction equations (GMPE) for regional studies. Cumulative probability plots and residual plots are used to check the normality and model inadequacies in various GMPE. It is seen that as long as the data set is similar to that used for generating GMPE the normality and model adequacies are broadly satisfied. However, clear deviation from normality is observed when using GMPE for predicting different data sets. In order to check utility of various worldwide GMPE for dataset other than that used for preparing GMPE, the dataset of Himalayan earthquakes recorded on strong motion network has been predicted using the GMPE given by Abrahamson and Litehiser (1989), Boore and Atkinson (2008), Boore et al. (1997) and Joyner and Boore (1981). It is seen that these GMPE shows presence of fat tails together with large model inadequacies when they are used for predicting Himalayan data. The data for Himalayan earthquake are also predicted by using the GMPE developed using Himalayan data. It is seen that this GMPE obeys normality and does not reflect any model inadequacies. The dependency of GMPE on the seismic zonation map of the region is also checked in this work. The seismic map for 10% probability of exceedence of peak ground acceleration of 0.1g is prepared using modified method given by Joshi and Patel (1997). It is seen that two different regional GMPE developed using Himalayan dataset gives similar seismic zonation map however large deviation in the seismic zonation map is observed when GMPE given by Abrahamson and Litehiser (1989) has been used.