Mathematical and Stochastic Growth Models

Many statistical and mathematical models of growth are developed in the literature and effectively applied to various conditions in the existent world that involve many research problems in the different fields of applied statistics. Nevertheless, still, there is an equally large number of conditions, which have not yet been mathematically or statistically modeled, due to the complex situations or formed models are mathematically or statistically inflexible. The present study is based on mathematical and stochastic growth models. The specification of both the growth models is depicted. A detailed study of newly modified growth models is mentioned. This research will give substantial information on growth models, such as proposed modified exponential growth models and their specifications clearly motioned which gives scope for future research.

Dynamics of notified cases of dengue in Alagoas: Geospatialization and Applied Statistics

The aim of the study was to evaluate the reported cases of dengue in the State of Alagoas via applied statistics and geospatialization.Dengue data were obtained from the DATASUS system between 2000 and 2015. The time series was submitted to descriptive and exploratory statistics and the Pettitt test. In the dengue case maps, the Spline method via QGis version 3.4 was used. In descriptive statistics, only 10 municipalities were evaluated based on the largest case records. All municipalities were above the average of dengue cases in 2010, the year of the biggest recent flood in the state. The boxplot pointed out that all 10 municipalities were positive asymmetric in a few months for dengue cases, the exception was Delmiro Gouveia. The Pettitt test identified biannual cycles (2006/2007 and 2009/2010) associated with the phases of ENSO (El Niño and La Niña) in the moderate category, followed by the months of January, February, April and December, corresponding to the performance of some systems synoptics. In the mapping of annual cases of dengue, the highest records occurred in the Agreste and East Alagoas. Geospatialization and applied statistics are efficient in the spatiotemporal evaluation of dengue cases in Alagoas.

Reflections on statistical modelling: A conversation with Murray Aitkin

A virtual interview with Murray Aitkin by Brian Francis and John Hinde, two of the original members of the Centre for Applied Statistics that Murray created at Lancaster University. The talk ranges over Murray's reflections of a career in statistical modelling and the many different collaborations across the world that have been such a significant part of it.

Сравнительный анализ критериев и методов определения тренда во временных рядах параметров регистрации технического состояния газотурбинных двигателей

The main directions of improving the processes of life cycle management of power and power plants based on gas turbine engines are based on the strategy of operation according to the technical state. The very concept of a technical condition and the need to assess the tendencies of its permissible change determine the use of applied statistics methods to establish such tendencies - trends. Trend analysis has now emerged as an independent direction in applied statistics due to the specifics of the research object and the importance of applied applications. The problematic issue of the implementation of the strategy for the operation of gas turbine engines according to the technical condition is the reasonable choice of such criteria and methods for determining the trend, which are most consistent with the objects of diagnostics. One of the most important tasks of time series analysis is to substantiate the statistical model of data generation. Such a model, or their combination, should adequately reflect the change in the properties of an object during long-term operation, take into account the features of power plants for aviation and ground use, as well as the experience of use according to the operation manual. The next task is to select and analyze the trend and randomness criteria in relation to the time series, consisting of the parameters for registering the technical state of gas turbine engines. The specificity of trend criteria lies in the fact that at a given level of significance, the hypothesis about the randomness of the time series can only be refuted. The study of an alternative encounters significant difficulties, since the presence of a trend turns a time series into a non-stationary random process. At the same time, the practice of application requires a rational combination of errors of the first (false alarm) and second (trend skipping) kind. Operation by technical condition creates the prerequisites for the use of modern trend analysis methods, which allow dividing the time series into components in accordance with the accepted statistical model of data generation. From the group of such methods, it is advisable to single out the methods of orthogonal decomposition (factor analysis, the method of principal components), since they allow making a predictive assessment of the development of a trend. However, the proposed methods are predominantly scalar in nature, while the initial data on the technical condition of gas turbine engines are multidimensional time series of output parameters related to each other. Comparative analysis of the criteria and methods for determining the trend in the time series of registration parameters is of great practical importance, since it allows increasing the reliability of statistical conclusions about the technical condition of gas turbine engines.

New Geometric Morphometric Insights in Digital Taphonomy: Analyses into the Sexual Dimorphism of Felids through Their Tooth Pits

Recent studies using geometric morphometrics for taphonomy have yielded interesting results, opening new horizons of research in both archaeological and paleontological sites. Here we present the analysis of tooth pits left by male and female individuals of two different carnivore species (Panthera tigris and Panthera pardus) in order to see if sexual dimorphism influences the morphology of tooth pit marks. In the process, 3D-scanning and applied statistics were used. Based on samples derived from two individuals of different sexes, the present results indicate sexual dimorphism in these felid species to not be a conditioning factor of tooth pit morphology.

Applied Statistics: Basic Principles and Application

Statistics is an old scientific discipline, but its application has never been more topical. Statistics is a branch of mathematics that deals with the collection, analysis, interpretation and presentation of data. Increased computing power had a huge impact on the popularisation of the practice of statistical science. With new technologies such as the internet of things, we start to collect data from various sources like web server logs, online transaction records, tweet streams, social media, data from all kinds of sensors. With increased access to big data, there is a need for professionals with applied statistics knowledge who can visualize and analyze data, make sense of it, and use it to solve real complex problems. Applied statistics is the root of data analysis, and the practice of applied statistics involves analyzing data to help define and determine organizational needs. Today we can find applied statistics in various fields such as medicine, information technology, engineering, finance, marketing, accounting, business, etc. The goal of this paper is to clarify the applied statistics, its principles and to present its application in various fields.

Change of paradigms in applied statistics

.

Recommendations for statistical methods usage for processing data of pedagogical experiments

In some institutions of continuous education in the Republic of Moldova there is no course in Applied Statistics for Teacher taught. Because of this, the graduates encounter some difficulties in processing the experimental data. Through this article, the authors propose suggestions and models for data processing for additional qualification / requalification theses.

Applied Statistics with R

Whether at the undergraduate, graduate, or post-graduate level, Applied Statistics with R: A Practical Guide for the Life Sciences teaches readers to properly analyze data in an efficient, accessible, plainspoken, frank, and occasionally humorous manner. Readers will come away with the knowledge of which analyses they should use and when they should use them, an important skill in an age when the statistical analyses used in the life-sciences are becoming increasingly advanced. This book uses the statistical language R, which is the choice of ecologists worldwide and is rapidly becoming the ‘go-to’ stats program throughout the life-sciences. Written around a single real-world dataset, Applied Statistics with R which encourages readers to become deeply familiar with an imperfect but realistic set of data, much like they themselves might collect. Early chapters are designed to teach basic data manipulation skills and build good habits in preparation for learning more advanced analyses. This approach also demonstrates the importance of viewing data through different lenses, facilitating an easy and natural progression from linear and generalized linear models through to mixed effects versions of those same analyses. Readers will also learn advanced plotting and data-wrangling techniques, and gain an introduction to writing their own functions. Applied Statistics with R is suitable for senior undergraduate and graduate students, professional researchers, and practitioners throughout the life-sciences, whether in the fields of ecology, evolution, environmental studies, or computational biology.