“Normality is threatened by the Monster”: Robin Wood, Romero and zombies

A tribute to Robin Wood, focusing on his influence on horror criticism, and more specifically, on his appraisal of George A. Romero as ‘a great and audacious filmmaker’ through detailed consideration of his zombie movies. The article considers the key elements of his extraordinary influence on horror criticism, and a detailed examination of the monster which most directly responds to horror’s potential ambivalence: the zombie. In order to consider the ambivalence in the relationship between normality and the monster – that central and most important component of Wood’s horror criticism – created by Romero’s zombies, analysis focuses on the materiality of the films through close attention to the bodies on-screen.

Normality under uncertainty

Consider the demand for a good whose consumption be chosen prior to the resolution of uncertainty regarding income. How do changes in the distribution of income affect the demand for this good? In this paper we show that normality, is sufficient to guarantee that consumption increases of the Radon-Nikodym derivative of the new distribution with respect to the old is non-decreasing in the whole domain. However, if only first order stochastic dominance is assumed more structure must be imposed on preferences to guanantee the validity of the result. Finally a converse of the first result also obtains. If the change in measure is characterized by non-decreasing Radon-Nicodyn derivative, consumption of such a good will always increase if and only if the good is normal.

Second-growth western white pine stands : site index and species changes, normality percentage trends, mortality /

Includes bibliographical references (p. 58-60).

Breaking down the non-normality of daily stock returns

This paper investigates whether the non-normality typically observed in daily stock-market returns could arise because of the joint existence of breaks and GARCH effects. It proposes a data-driven procedure to credibly identify the number and timing of breaks and applies it on the benchmark stock-market indices of 27 OECD countries. The findings suggest that a substantial element of the observed deviations from normality might indeed be due to the co-existence of breaks and GARCH effects. However, the presence of structural changes is found to be the primary reason for the non-normality and not the GARCH effects. Also, there is still some remaining excess kurtosis that is unlikely to be linked to the specification of the conditional volatility or the presence of breaks. Finally, an interesting sideline result implies that GARCH models have limited capacity in forecasting stock-market volatility.

Criterion of Normality of the Completely Regular Topology of Separate Continuity

2000 Mathematics Subject Classification: 54C10, 54D15, 54G12.

On Quasi-Normality of Two-Sided Multiplication

2000 Mathematics Subject Classification: 47B47, 47B10, 47A30.

An Assessment of the Performances of Several Univariate Tests of Normality

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.

From exotic seduction to utter normality : Discourse research and International Relations

Peer reviewed

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

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.

Reducing the risk of posttraumatic stress disorder in children following natural disasters

A significant number of children suffer long term psychological disturbance following exposure to a natural disaster. Evidence suggests that a dose-response relationship exists, so that children and adolescents who experience the most intense or extensive exposure to the risk factors for PTSD are likely to develop the most serious and persistent symptoms. Risk factors include gender, age, personality, extent of exposure to the natural disaster, amount of damage to property and infrastructure, witnessing injury or death of others or perceiving a threat to their own life. Knowing these factors enables various strategies to be put in place to decrease the risk of psychological disturbance following the aftermath of traumatic events. Re-establishing a sense of safety, security and normality is important in the aftermath of a natural disaster, and promoting social connectedness, positive family functioning, and effective coping mechanisms can make children more resilient in the face of catastrophic events. This paper examines the risk and protective factors associated with the development of post traumatic stress disorder (PTSD), and considers how schools can use this knowledge to contribute to the recovery effort, and reduce the prevalence of PTSD amongst pupils in the wake of a natural disaster.

Bootstrap approaches for estimation and confidence intervals of long term memory processes

In this work, we investigate an alternative bootstrap approach based on a result of Ramsey [F.L. Ramsey, Characterization of the partial autocorrelation function, Ann. Statist. 2 (1974), pp. 1296-1301] and on the Durbin-Levinson algorithm to obtain a surrogate series from linear Gaussian processes with long range dependence. We compare this bootstrap method with other existing procedures in a wide Monte Carlo experiment by estimating, parametrically and semi-parametrically, the memory parameter d. We consider Gaussian and non-Gaussian processes to prove the robustness of the method to deviations from normality. The approach is also useful to estimate confidence intervals for the memory parameter d by improving the coverage level of the interval.

Modelling Spikes in Electricity Prices

uring periods of market stress, electricity prices can rise dramatically. Electricity retailers cannot pass these extreme prices on to customers because of retail price regulation. Improved prediction of these price spikes therefore is important for risk management. This paper builds a time-varying-probability Markov-switching model of Queensland electricity prices, aimed particularly at forecasting price spikes. Variables capturing demand and weather patterns are used to drive the transition probabilities. Unlike traditional Markov-switching models that assume normality of the prices in each state, the model presented here uses a generalised beta distribution to allow for the skewness in the distribution of electricity prices during high-price episodes.