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Copyright of Polish Statistician / Wiadomości Statystyczne is the property of State Treasury - Statistics Poland and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Polish Statistician / Wiadomości Statystyczne is the property of State Treasury - Statistics Poland and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The use of statistical methods in the diagnosis of production processes dates back to the beginning of the 20th century. Widespread computerization of processes made enterprises face the challenge of processing large sets of measurement data. The growing number of sensors on production lines requires the use of faster and more effective methods of both process diagnostics and finding connections between individual systems. This article is devoted to the use of Python libraries to effectively solve some problems related to the analysis of large data sets. The article is based on the experience related to data analysis in a large company in the automotive industry, whose annual production reaches 10 million units. The methods described in this publication were the basis for the initial analysis of production data in the plant, and the obtained results fed the production database and the created automatic anomaly detection system based on artificial intelligence algorithms. [ABSTRACT FROM AUTHOR]

Copyright of Management Issues / Problemy Zarządzania is the property of Problemy Zarzadzania and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Despite the numerous papers on the statistical analyses o fpH, there is no explicit opinion on the use of arithmetic mean as a measure of the central tendency for pH and H+ activity. The problem arises because the transformation of the arithmetic mean for one does not give the arithmetic mean for the other. The paper presents 1) the theoretical considerations on the distribution of pH and H+ activity and relation between them, properties of these distributions, the choice of distributions which should be consistent with the distribution of pH and the distribution of H+ activity and measures of central tendency for features of such distributions and 2) examples of calculations of measures of central tendency for pH and H+ activity based on the literature data on soil and lake water pH. These data analyses included distributions of pH and H+ activities, properties of distribution, descriptive statistics for pH and for the H+ activity and comparison of arithmetic mean with the geometric mean. From the results, it could be concluded that a uniform approach to the choice of measure for the central tendency of pH and H+ activity requires the determination of the type of measure (mean) for one of them and then consistent transformation of this measure. The choice of measure of the central tendency for the variable should be preceded by determination of its distribution. Normal probability distribution of pH and thus lognormal distribution of H+ activity indicate that the arithmetic mean, and its corresponding geometric mean should be used as proper measures of the central tendency for pH and for H+ activity. Besides, the position statistic that is a median can be used for each of those variables, irrespective of their probability distributions. [ABSTRACT FROM AUTHOR]

The article presents the results of research into the transformation of series of hydro-meteorological data for determining dry periods with the Standardised Precipitation Index (SPI) and the Standardised Discharge Index (SDI). Time series from eight precipitation stations and five series of river discharge data in Eastern Kujawy (central Poland) were analysed for 1951–2010. The frequency distribution of the series for their convergence with the normal distribution was tested with the Shapiro–Wilk test and homogeneity with the Bartlett's test. The transformation of the series was done with the Box–Cox technique, which made it possible to homogenise the series in terms of variance. In Poland, the technique has never been used to determine the SPI. After the transformation the distributions of virtually all series complied with the normal distribution and were homogeneous. Moreover, a statistically significant correlation between the δ transformation parameter and the skewness of the series of monthly precipitation was observed. It was similar for the series of mean monthly discharges in the winter half-year and the hydrological year. The analysis indicates an alternate occurrence of dry and wet periods both in case of precipitation and run-offs. Drought periods coincided with low flow periods. Thus, the fluctuations tend to affect the development of agriculture more than long-term ones.

Copyright of Przegląd Elektrotechniczny is the property of Przeglad Elektrotechniczny and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Safety & Fire Technology / Bezpieczeństwo i Technika Pożarnicza is the property of Centrum Naukowo-Badawcze Ochrony Przeciwpozarowej and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

Copyright of Econometrics / Ekonometria is the property of Sciendo and its content may not be copied or emailed to multiple sites or posted to a listserv without the copyright holder's express written permission. However, users may print, download, or email articles for individual use. This abstract may be abridged. No warranty is given about the accuracy of the copy. Users should refer to the original published version of the material for the full abstract. (Copyright applies to all Abstracts.)

The paper discusses studentized sample mean distribution. The sample is from exponential distribution. On the basis of independent replications of the samples empirical distributions studentized mean was calculated. The distance between the empirical distributions and the standard normal distribution was measured by means well known as statistics of Kolmogorov. Under the appropriate sample sizes the degree of the difference between the empirical and theoretical distributions was evaluated. Moreover, the hypothesis on normality of the empirical distributions was tested by means of the Kolmogorov test. [ABSTRACT FROM AUTHOR]