Study on Key Biological Indicators of Diabetes Based on Statistical Tests

Normality testing is a fundamental hypothesis test in the statistical analysis of key biological indicators of diabetes.If this assumption is violated,it may cause the test results to deviate from the true value,leading to incorrect inferences and conclusions,and ultimately affecting the validity and accuracy of statistical inferences.Considering this,the study designs a unified analysis scheme for different data types based on parametric statistical test methods and non-parametric test methods.The data were grouped according to sample type and divided into discrete data and continuous data.To account for differences among subgroups,the conventional chi-squared test was used for discrete data.The normal distribution is the basis of many statistical methods;if the data does not follow a normal distribution,many statistical methods will fail or produce incorrect results.Therefore,before data analysis and modeling,the data were divided into normal and non-normal groups through normality testing.For normally distributed data,parametric statistical methods were used to judge the differences between groups.For non-normal data,non-parametric tests were employed to improve the accuracy of the analysis.Statistically significant indicators were retained according to the significance index P-value of the statistical test or corresponding statistics.These indicators were then combined with relevant medical background to further explore the etiology leading to the occurrence or transformation of diabetes status.

STATISTICAL TESTS FOR THE COMPARISON OF THE INCIDENCE OR MORTALITY RATES IN CANCER REGISTRY AND DESCRIPTIVE EPIDEMIOLOGY──A MICROCOMPUTER PROGRAM IN BASIC

This paper describes the statistical methods of the comparison of the incidence or mortality rates in cancer registry and descriptive epidemiology, and the features of microcomputer program (CANTEST) which was designed to perform the methods. The program was written in IBM BASIC language. Using the program CANTEST we presented here the user can do several statistical tests or estimations as follow: 1. the comparison of the adjusted rates which were calculated by directly or indirectly standardized methods, 2. the calculation of the slope of regression line for testing the linear trends of the adjusted rates, 3. the estimation of the 95% or 99%conndence intervals of the directly adjusted rates, of the cumulative rates (0-64 and 0-74), and of the cumulative risk. Several examples are presented for testing the performances of the program.

A Comprehensive Guide for Selecting Appropriate Statistical Tests: Understanding When to Use Parametric and Nonparametric Tests

Choosing appropriate statistical tests is crucial but deciding which tests to use can be challenging. Different tests suit different types of data and research questions, so it is important to choose the right one. Knowing how to select an appropriate test can lead to more accurate results. Invalid results and misleading conclusions may be drawn from a study if an incorrect statistical test is used. Therefore, to avoid these it is essential to understand the nature of the data, the research question, and the assumptions of the tests before selecting one. This is because there are a wide variety of tests available. This paper provides a step-by-step approach to selecting the right statistical test for any study, with an explanation of when it is appropriate to use it and relevant examples of each statistical test. Furthermore, this guide provides a comprehensive overview of the assumptions of each test and what to do if these assumptions are violated.

A Comprehensive Guide for Selecting Appropriate Statistical Tests: Understanding When to Use Parametric and Nonparametric Tests

Choosing appropriate statistical tests is crucial but deciding which tests to use can be challenging. Different tests suit different types of data and research questions, so it is important to choose the right one. Knowing how to select an appropriate test can lead to more accurate results. Invalid results and misleading conclusions may be drawn from a study if an incorrect statistical test is used. Therefore, to avoid these it is essential to understand the nature of the data, the research question, and the assumptions of the tests before selecting one. This is because there are a wide variety of tests available. This paper provides a step-by-step approach to selecting the right statistical test for any study, with an explanation of when it is appropriate to use it and relevant examples of each statistical test. Furthermore, this guide provides a comprehensive overview of the assumptions of each test and what to do if these assumptions are violated.

A novel method for clustering cellular data to improve classification

Many fields,such as neuroscience,are experiencing the vast prolife ration of cellular data,underscoring the need fo r organizing and interpreting large datasets.A popular approach partitions data into manageable subsets via hierarchical clustering,but objective methods to determine the appropriate classification granularity are missing.We recently introduced a technique to systematically identify when to stop subdividing clusters based on the fundamental principle that cells must differ more between than within clusters.Here we present the corresponding protocol to classify cellular datasets by combining datadriven unsupervised hierarchical clustering with statistical testing.These general-purpose functions are applicable to any cellular dataset that can be organized as two-dimensional matrices of numerical values,including molecula r,physiological,and anatomical datasets.We demonstrate the protocol using cellular data from the Janelia MouseLight project to chara cterize morphological aspects of neurons.

A New Statistical Approach to Assess Climate Variability in the White Bandama Watershed,Northern Cote d’Ivoire

The population of northern C&#244te d’Ivoire, especially in the white Bandama watershed, lives for majority in rural areas and depends on farming, which is mainly linked to climate variability. This study evaluates the trends within watershed’s hydro-climatic variables and their level of significance over the period 1950-2000. The methodological approach consists in applying successively standardized indexes to detect trends and breaks in hydro-climatic long-term data. The Mann-Kendall statistical test lets us know the trends significance and the Kendall-Theil Robust Line test reveals their magnitude. The Student’s t test underlines break years. Results show that although rainfall has decreased, this decline is not statistically significant. However, temperature and potential evapotranspiration have strongly rised and discharge was submitted to high decline. These changes in hydrometeorological variables appeared from 1970 to 1980. This study is different from others conducted on climate variability in the northern C&#244te d’Ivoire by the methodological statistical framework implemented and the understanding of significance level of climate trends. Until now, authors used the standardized index to detect trends in hydro-climatic parameters. For this work, we added the Mann-Kendall statistical test to assess the significance level of these trends at α = 5% and 10%. Then, the Kendall-Theil statistical test was used to highlight the trends magnitude and the student’s t test to know the break years.

Reply to 'Statistical testing and distribution for lead chloride toxicity'

We are very grateful for the letter written by Dr Lange,and indeed apologize for the mistakes noted in the word-ing of our text regarding statistical analysis.This wasdue to changes carried out while revising the manuscriptat the request of reviewers,whom we thank for,point-ing out several issues that were actually similar to thosenoted by Dr.Lange.Unfortunately,we were unable todescribe and discuss our findings properly in the context

Effectiveness Assessment of the Search-Based Statistical Structural Testing

Search-based statistical structural testing(SBSST)is a promising technique that uses automated search to construct input distributions for statistical structural testing.It has been proved that a simple search algorithm,for example,the hill-climber is able to optimize an input distribution.However,due to the noisy fitness estimation of the minimum triggering probability among all cover elements(Tri-Low-Bound),the existing approach does not show a satisfactory efficiency.Constructing input distributions to satisfy the Tri-Low-Bound criterion requires an extensive computation time.Tri-Low-Bound is considered a strong criterion,and it is demonstrated to sustain a high fault-detecting ability.This article tries to answer the following question:if we use a relaxed constraint that significantly reduces the time consumption on search,can the optimized input distribution still be effective in faultdetecting ability?In this article,we propose a type of criterion called fairnessenhanced-sum-of-triggering-probability(p-L1-Max).The criterion utilizes the sum of triggering probabilities as the fitness value and leverages a parameter p to adjust the uniformness of test data generation.We conducted extensive experiments to compare the computation time and the fault-detecting ability between the two criteria.The result shows that the 1.0-L1-Max criterion has the highest efficiency,and it is more practical to use than the Tri-Low-Bound criterion.To measure a criterion’s fault-detecting ability,we introduce a definition of expected faults found in the effective test set size region.To measure the effective test set size region,we present a theoretical analysis of the expected faults found with respect to various test set sizes and use the uniform distribution as a baseline to derive the effective test set size region’s definition.

Statistical analyses for NANOGrav 5-year timing residuals

In pulsar timing, timing residuals are the differences between the observed times of arrival and predictions from the timing model. A comprehensive timing model will produce featureless resid- uals, which are presumably composed of dominating noise and weak physical effects excluded from the timing model （e.g. gravitational waves）. In order to apply optimal statistical methods for detecting weak gravitational wave signals, we need to know the statistical properties of noise components in the residuals. In this paper we utilize a variety of non-parametric statistical tests to analyze the whiteness and Gaussianity of the North American Nanohertz Observatory for Gravitational Waves （NANOGrav） 5- year timing data, which are obtained from Arecibo Observatory and Green Bank Telescope from 2005 to 2010. We find that most of the data are consistent with white noise; many data deviate from Gaussianity at different levels, nevertheless, removing outliers in some pulsars will mitigate the deviations.

Remote Sensing Image Retrieval Based on 3D-Local Ternary Pattern(LTP)Features and Non-subsampled Shearlet Transform(NSST)Domain Statistical Features

With the increasing popularity of high-resolution remote sensing images,the remote sensing image retrieval(RSIR)has always been a topic of major issue.A combined,global non-subsampled shearlet transform(NSST)-domain statistical features(NSSTds)and local three dimensional local ternary pattern(3D-LTP)features,is proposed for high-resolution remote sensing images.We model the NSST image coefficients of detail subbands using 2-state laplacian mixture(LM)distribution and its three parameters are estimated using Expectation-Maximization(EM)algorithm.We also calculate the statistical parameters such as subband kurtosis and skewness from detail subbands along with mean and standard deviation calculated from approximation subband,and concatenate all of them with the 2-state LM parameters to describe the global features of the image.The various properties of NSST such as multiscale,localization and flexible directional sensitivity make it a suitable choice to provide an effective approximation of an image.In order to extract the dense local features,a new 3D-LTP is proposed where dimension reduction is performed via selection of‘uniform’patterns.The 3D-LTP is calculated from spatial RGB planes of the input image.The proposed inter-channel 3D-LTP not only exploits the local texture information but the color information is captured too.Finally,a fused feature representation(NSSTds-3DLTP)is proposed using new global(NSSTds)and local(3D-LTP)features to enhance the discriminativeness of features.The retrieval performance of proposed NSSTds-3DLTP features are tested on three challenging remote sensing image datasets such as WHU-RS19,Aerial Image Dataset(AID)and PatternNet in terms of mean average precision(MAP),average normalized modified retrieval rank(ANMRR)and precision-recall(P-R)graph.The experimental results are encouraging and the NSSTds-3DLTP features leads to superior retrieval performance compared to many well known existing descriptors such as Gabor RGB,Granulometry,local binary pattern(LBP),Fisher vector(FV),vector of locally aggregated descriptors(VLAD)and median robust extended local binary pattern(MRELBP).For WHU-RS19 dataset,in terms of{MAP,ANMRR},the NSSTds-3DLTP improves upon Gabor RGB,Granulometry,LBP,FV,VLAD and MRELBP descriptors by{41.93%,20.87%},{92.30%,32.68%},{86.14%,31.97%},{18.18%,15.22%},{8.96%,19.60%}and{15.60%,13.26%},respectively.For AID,in terms of{MAP,ANMRR},the NSSTds-3DLTP improves upon Gabor RGB,Granulometry,LBP,FV,VLAD and MRELBP descriptors by{152.60%,22.06%},{226.65%,25.08%},{185.03%,23.33%},{80.06%,12.16%},{50.58%,10.49%}and{62.34%,3.24%},respectively.For PatternNet,the NSSTds-3DLTP respectively improves upon Gabor RGB,Granulometry,LBP,FV,VLAD and MRELBP descriptors by{32.79%,10.34%},{141.30%,24.72%},{17.47%,10.34%},{83.20%,19.07%},{21.56%,3.60%},and{19.30%,0.48%}in terms of{MAP,ANMRR}.The moderate dimensionality of simple NSSTds-3DLTP allows the system to run in real-time.

Association between people’s attitudes towards human-elephant conflict and their locational,demographic,and socio-economic characteristics in Buxa Tiger Reserve and its adjoining area,India

“Human-elephant conflict(HEC)”,the alarming issue,in present day context has attracted the attention of environmentalists and policy makers.The rising conflict between human beings and wild elephants is common in Buxa Tiger Reserve(BTR)and its adjoining area in West Bengal State,India,making the area volatile.People’s attitudes towards elephant conservation activity are very crucial to get rid of HEC,because people’s proximity with wild elephants’habitat can trigger the occurrence of HEC.The aim of this study is to conduct an in-depth investigation about the association of people’s attitudes towards HEC with their locational,demographic,and socio-economic characteristics in BTR and its adjoining area by using Pearson’s bivariate chi-square test and binary logistic regression analysis.BTR is one of the constituent parts of Eastern Doors Elephant Reserve(EDER).We interviewed 500 respondents to understand their perceptions to HEC and investigated their locational,demographic,and socio-economic characteristics including location of village,gender,age,ethnicity,religion,caste,poverty level,education level,primary occupation,secondary occupation,household type,and source of firewood.The results indicate that respondents who are living in enclave forest villages(EFVs),peripheral forest villages(PFVs),corridor village(CVs),or forest and corridor villages(FCVs),mainly males,at the age of 18–48 years old,engaged with agriculture occupation,and living in kancha and mixed houses,have more likelihood to witness HEC.Besides,respondents who are illiterate or at primary education level are more likely to regard elephant as a main problematic animal around their villages and refuse to participate in elephant conservation activity.For the sake of a sustainable environment for both human beings and wildlife,people’s attitudes towards elephants must be friendly in a more prudent way,so that the two communities can live in harmony.

Estimation of Daily Global Solar Radiation with Different Sunshine-Based Models for Some Burundian Stations

Sunshine duration (S) based empirical equations have been employed in this study to estimate the daily global solar radiation on a horizontal surface (G) for six meteorological stations in Burundi. Those equations include the Ångström-Prescott linear model and four amongst its derivatives, i.e. logarithmic, exponential, power and quadratic functions. Monthly mean values of daily global solar radiation and sunshine duration data for a period of 20 to 23 years, from the Geographical Institute of Burundi (IGEBU), have been used. For any of the six stations, ten single or double linear regressions have been developed from the above-said five functions, to relate in terms of monthly mean values, the daily clearness index () to each of the next two kinds of relative sunshine duration (RSD): and . In those ratios, G0, S0 and stand for the extraterrestrial daily solar radiation on a horizontal surface, the day length and the modified day length taking into account the natural site’s horizon, respectively. According to the calculated mean values of the clearness index and the RSD, each station experiences a high number of fairly clear (or partially cloudy) days. Estimated values of the dependent variable (y) in each developed linear regression, have been compared to measured values in terms of the coefficients of correlation (R) and of determination (R2), the mean bias error (MBE), the root mean square error (RMSE) and the t-statistics. Mean values of these statistical indicators have been used to rank, according to decreasing performance level, firstly the ten developed equations per station on account of the overall six stations, secondly the six stations on account of the overall ten equations. Nevertheless, the obtained values of those indicators lay in the next ranges for all the developed sixty equations:;;;, with . These results lead to assert that any of the sixty developed linear regressions (and thus equations in terms of and ), fits very adequately measured data, and should be used to estimate monthly average daily global solar radiation with sunshine duration for the relevant station. It is also found that using as RSD, is slightly more advantageous than using for estimating the monthly average daily clearness index, . Moreover, values of statistical indicators of this study match adequately data from other works on the same kinds of empirical equations.

Temperature Variation and Mutation Analysis over the Past 59 Years in Shenyang

In this paper,based on the observation data of air temperature during 1951-2009 in Shenyang,the interannual and interdecadal variation of annual average temperature,maximum and minimum temperature in Shenyang were conducted the statistical analysis by means of linear trend estimation and mutation detection by using Mann-Kendall method.As was demonstrated in the results,the annual average temperature,maximum and minimum temperature in Shenyang showed an upward trend,whose linear tendency rate was 0.231,0.181 and 0.218 respectively.The increment trend of annual average temperature,maximum and minimum temperature was extremely clear.The increase in minimum temperature was more significant than that in mean temperature and maximum temperature.The abrupt change point of annual mean temperature in Shenyang appeared in 1981;the abrupt change point of annual mean maximum temperature appeared in 1994;the annual mean minimum temperature underwent mutation in 1978.

Statistic Analysis of the Annual Extreme Wave Parameters for the Coast of China

According to the need of project design for offshore engineering and coastal engineering, this paper statistically analyses the annual extreme data of waves acquired at 19 observation stations along the coast of China. Five kinds of distribution curves are adopted: Pearson III (P-III), Log-Extreme I (LE), Log-Normal(LN), Weibull(W) and Exponential Γ(EΓ) to check the adaptability to the long-term distribution of annual extreme of wave in the China Sea areas. The New Curve Fitting Method (NFIT) method and Probability Weighted Moments (PWM) method are used to estimate the distribution parameters and thereby to derive the design wave parameters with different return periods at 19 observation stations. The test results show that by combining EΓ distribution and NFIT parameter estimation and optimum seeking by computer, the design wave parameters can be estimated with high accuracy, high speed and high efficiency, and the randomness of the estimated results can be avoided.

Archery Algorithm:A Novel Stochastic Optimization Algorithm for Solving Optimization Problems

Finding a suitable solution to an optimization problem designed in science is a major challenge.Therefore,these must be addressed utilizing proper approaches.Based on a random search space,optimization algorithms can find acceptable solutions to problems.Archery Algorithm(AA)is a new stochastic approach for addressing optimization problems that is discussed in this study.The fundamental idea of developing the suggested AA is to imitate the archer’s shooting behavior toward the target panel.The proposed algorithm updates the location of each member of the population in each dimension of the search space by a member randomly marked by the archer.The AA is mathematically described,and its capacity to solve optimization problems is evaluated on twenty-three distinct types of objective functions.Furthermore,the proposed algorithm’s performance is compared vs.eight approaches,including teaching-learning based optimization,marine predators algorithm,genetic algorithm,grey wolf optimization,particle swarm optimization,whale optimization algorithm,gravitational search algorithm,and tunicate swarm algorithm.According to the simulation findings,the AA has a good capacity to tackle optimization issues in both unimodal and multimodal scenarios,and it can give adequate quasi-optimal solutions to these problems.The analysis and comparison of competing algorithms’performance with the proposed algorithm demonstrates the superiority and competitiveness of the AA.

Testing and Evaluation for Web Usability Based on Extended Markov Chain Model

As the increasing popularity and complexity of Web applications and the emergence of their new characteristics, the testing and maintenance of large, complex Web applications are becoming more complex and difficult. Web applications generally contain lots of pages and are used by enormous users. Statistical testing is an effective way of ensuring their quality. Web usage can be accurately described by Markov chain which has been proved to be an ideal model for software statistical testing. The results of unit testing can be utilized in the latter stages, which is an important strategy for bottom-to-top integration testing, and the other improvement of extended Markov chain model (EMM) is to present the error type vector which is treated as a part of page node. this paper also proposes the algorithm for generating test cases of usage paths. Finally, optional usage reliability evaluation methods and an incremental usability regression testing model for testing and evaluation are presented. Key words statistical testing - evaluation for Web usability - extended Markov chain model (EMM) - Web log mining - reliability evaluation CLC number TP311. 5 Foundation item: Supported by the National Defence Research Project (No. 41315. 9. 2) and National Science and Technology Plan (2001BA102A04-02-03)Biography: MAO Cheng-ying (1978-), male, Ph.D. candidate, research direction: software testing. Research direction: advanced database system, software testing, component technology and data mining.

The Relationships between Variations of Sea Surface Temperature Anomalies in the Key Ocean Areas and the Precipitation and Surface Air Temperature in China

The relationships between variations of sea surface temperature anomalies (SSTVA) in the key ocean areas and the precipitation / temperature anomalies in China are studied based on the monthly mean sea surface temperature data from January 1951 to December 1998 and the same stage monthly mean precipitation/ temperature data of 160 stations in China. The purpose of the present study is to discuss whether the relationship between SSTVA and precipitation / temperature is different from that between sea surface temperature anomalies (SSTA) and precipitation/ temperature, and whether the uncertainty of prediction can be reduced by use of SSTVA. The results show that the responses of precipitation anomalies to the two kinds of tendency of SSTA are different. This implies that discussing the effects of two kinds of tendency of SSTA on precipitation anomalies is better than just discussing the effects of SSTA on precipitation anomalies. It helps to reduce the uncertainty of prediction. The temperature anomalies have more identical re-sponses to the two kinds of tendency of SSTA than the precipitation except in the western Pacific Ocean. The response of precipitation anomalies to SSTVA is different from that to SSTA, but there are some similarities. Key words Variations of sea surface temperature anomalies - Precipitation anomalies - Temperature anomalies - Statistical significance test Sponsored jointly by the “ National Key Developing Program for Basic Sciences” (G1998040900) Part I and the Key Program of National Nature Science Foundation of China “ Analyses and Mechanism Study of the Regional Climatic Change in China” under Grant No.49735170.

Memcapacitor model and its application in a chaotic oscillator

A memcapacitor is a new type of memory capacitor. Before the advent of practical memcapacitor, the prospective studies on its models and potential applications are of importance. For this purpose, we establish a mathematical memca- pacitor model and a corresponding circuit model. As a potential application, based on the model, a memcapacitor oscillator is designed, with its basic dynamic characteristics analyzed theoretically and experimentally. Some circuit variables such as charge, flux, and integral of charge, which are difficult to measure, are observed and measured via simulations and exper- iments. Analysis results show that besides the typical period-doubling bifurcations and period-3 windows, sustained chaos with constant Lyapunov exponents occurs. Moreover, this oscillator also exhibits abrupt chaos and some novel bifurcations. In addition, based on the digital signal processing （DSP） technology, a scheme of digitally realizing this memcapacitor os- cillator is provided. Then the statistical properties of the chaotic sequences generated from the oscillator are tested by using the test suit of the National Institute of Standards and Technology （NIST）. The tested randomness definitely reaches the standards of NIST, and is better than that of the well-known Lorenz system.

A CLASS OF RANDOM NUMBER GENERATORS BASED ON WEYL SEQUENCE

The generation of good pseudo-random numbers is the base of many important fields in scientific computing, such as randomized algorithms and numerical solution of stochastic differential equations. In this paper, a class of random number generators （RNGs） based on Weyl sequence is proposed. The uniformity of those RNGs is proved theoretically. Statistical and numerical computations show the efficiency of the methods.

INFLUENCE FACTORS AND PREDICTION METHOD ON FLOOD/DROUGHT DURING THE ANNUALLY FIRST RAINY SEASON IN SOUTH CHINA

By using the significance test of two-dimensional wind field anomalies and Monte Carlo simulation experiment scheme, the significance features of wind field anomalies are investigated in relation to flood/drought during the annually first rainy season in south China. Results show that westem Pacific subtropical high and wind anomalies over the northeast of Lake Baikal and central Indian Ocean are important factors. Wind anomalies over the northem India in January and the northwest Pacific in March may be strong prediction signals. Study also shows that rainfall in south China bears a close relation to the geopotential height filed over the northern Pacific in March.