Statistics for the Corrosionist
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Two-parameter models of fractional statistics aimed at finding an expression for the occupation numbers of free anyons have been considered. Virial coefficients are found for statistics of several types: к-deformed Polychronakos and Haldane–Wu statistics, Polychronakos and Haldane–Wu statistics modified with the q-exponential in the bosonic limit, and incomplete and nonadditive Gentile statistics for various level-filling maxima. A relation between the anyonic statistics and various statistics of fractional types is found and analyzed.
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INTRODUCTION When conducting a meta-analysis that includes previously published data, differences between treatments reported with P-values, least significant differences (LSD), and other statistics provide no direct estimate of the variance. ESTIMATING STANDARD ERROR FROM OTHER SUMMARY STATISTICS (_P_, _LSD_, _MSD_) In the context of the statistical meta-analysis models that we use, overestimates of variance are okay, because this effectively reduces the weight of a study in the overall analysis relative to an exact estimate, but provides more information than either excluding the study or excluding any estimate of uncertainty (though there are limits to this assumption such as ...). Where available, direct estimates of variance are preferred, including Standard Error (SE), sample Standard Deviation (SD), or Mean Squared Error (MSE). SE is usually presented in the format of mean (±SE). MSE is usually presented in a table. When extracting SE or SD from a figure, measure from the mean to the upper or lower bound. This is different than confidence intervals and range statistics (described below), for which the entire range is collected. If MSE, SD, or SE are not provided, it is possible that LSD, MSD, HSD, or CI will be provided. These are range statistics and the most frequently found range statistics include a Confidence Interval (95%CI), Fisher’s Least Significant Difference (LSD), Tukey’s Honestly Significant Difference (HSD), and Minimum Significant Difference (MSD). Fundamentally, these methods calculate a range that indicates whether two means are different or not, and this range uses different approaches to penalize multiple comparisons. The important point is that these are ranges and that we record the entire range. Another type of statistic is a “test statistic”; most frequently there will be an F-value that can be useful, but this should not be recorded if MSE is available. Only if there is no other information available should you record the P-value.
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We made in this paper a brief analysis of the following statistics: Intermediate Statistics, Parastatistics, Fractionary Statistics and Gentileonic Statistics that predict the existence of particles which are different from bosons, fermions and maxwellons. We shown the fundamental hypothesis assumed in each one of the above mentioned statistics and their main predictions and compared them with experimental results. Taking into account the works done about these statistics we could say that there is a tendency to believe that real particles, that is, those that can be observed freely, can be only bosons, fermions and maxwellons and that all other particles, different from these would be quasiparticles. Up to date in 3-dim systems only bosons, fermions and maxwellons have been detected freely. Recently in 2-dim systems have been detected the quasiparticles named anyons that have fractionary charges and spins.
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Abstract This article explores the use of t statistics based on two-or four-order statistics. The functions of the order statistics, which are used to define the t statistics, are the pivots and bipivots. The pivots are exact order statistics, while the bipivots are the means of two adjacent order statistics. Two t statistics, based on the pivots and bipivots, are examined and compared to other t statistics, including Student's t, under various sampling situations. We conclude that the proposed t statistics are not only simple to use but are robust and perform quite well in terms of the lengths of their confidence intervals. We recommend that these t statistics be used for sample sizes between 4 and 20, because they perform well and are easy to use. Tables of percentage points are provided to facilitate the use of the t statistics.
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Бұл зерттеужұмысындaКaно моделітурaлы жәнеоғaн қaтыстытолықмәліметберілгенжәнеуниверситетстуденттерінебaғыттaлғaн қолдaнбaлы (кейстік)зерттеужүргізілген.АхметЯссaуи университетініңстуденттеріүшін Кaно моделіқолдaнылғaн, олaрдың жоғaры білімберусaпaсынa қоятынмaңыздытaлaптaры, яғнисaпaлық қaжеттіліктері,олaрдың мaңыздылығытурaлы жәнесaпaлық қaжеттіліктерінеқaтыстыөз университетінқaлaй бaғaлaйтындығытурaлы сұрaқтaр қойылғaн. Осы зерттеудіңмaқсaты АхметЯсaуи университетіндетуризмменеджментіжәнеқaржы бaкaлaвриaт бaғдaрлaмaлaрыныңсaпaсынa қaтыстыстуденттердіңқaжеттіліктерінaнықтaу, студенттердіңқaнaғaттaну, қaнaғaттaнбaу дәрежелерінбелгілеу,білімберусaпaсын aнықтaу мен жетілдіружолдaрын тaлдaу болыптaбылaды. Осы мaқсaтқaжетуүшін, ең aлдыменКaно сaуaлнaмaсы түзіліп,116 студенткеқолдaнылдыжәнебілімберугежәнеоның сaпaсынa қaтыстыстуденттердіңтaлaптaры мен қaжеттіліктерітоптықжұмыстaрaрқылыaнықтaлды. Екіншіден,бұл aнықтaлғaн тaлaптaр мен қaжеттіліктерКaно бaғaлaу кестесіменжіктелді.Осылaйшa, сaпa тaлaптaры төрт сaнaтқa бөлінді:болуытиіс, бір өлшемді,тaртымдыжәнебейтaрaп.Соңындa,қaнaғaттaну мен қaнaғaттaнбaудың мәндеріесептелдіжәнестуденттердіңқaнaғaттaну мен қaнaғaттaнбaу деңгейлерінжоғaрылaту мен төмендетудеосытaлaптaр мен қaжеттіліктердіңрөліaйқын aнықтaлды.Түйінсөздер:сaпa, сaпaлық қaжеттіліктер,білімберусaпaсы, Кaно моделі.
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Kurtosis
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The traditional way for statistics in any statistical book starting with descriptive statistics, followed by Probability and ends with inferential Statistics. The probability is considered as the link between descriptive and inferential statistics. Inferential Statistics has wide definition and is defined as “the branch of statistics concerned with using sample data to make inferences about a population. In inferential statistics, predictions are made and conclusions are drawn for the target population based on the sample”. The main topics of inferential statistics are Estimation, Testing Hypotheses about means, variances, goodness of fit and proportions, Correlation, Regression and Time series. In this article we are trying to organize the statistics by splitting the inferential statistics into two parts, namely Diagnostic Statistics and Predictive Statistics and explaining the importance of each part. Also we will discuss a Perspective Statistics. Based on that we will have four levels in statistics that can be used to analyze data (Descriptive, Diagnostic, Predictive and Perspective Statistics). Descriptive statistics are primarily concerned with graphs, frequency tables, measures of central tendency, measures of variation, and measures of shape. Diagnostic statistics are primarily concerned with the effects of the Independent variables (inputs) on the Dependent (Target) variable, as measured by Tests of Correlation or Association, Tests for Mean Differences, and Tests for Classification. Predictive statistics are primarily concerned with estimation, regression techniques, and time series analysis for the dependent (target) variable. Perspective statistics mainly related to the previous three levels and acts as a prescription to how to solve or prevent the problem, which means to take a decision in advance. In this article, we will clarify idea through giving an example on a real data related to Gynecologic Cancer, and show how the perspective analytics can prevent it.
Statistical Inference
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