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The purpose of this study was to identify the factors affecting the production companies in the laminate flooring industry in terms of competitiveness using nonparametric tests. The statistical population of this research includes experts and specialists in two areas of competitiveness and structure of the laminate flooring industry; managers in companies producing and importing this product and customers of laminate flooring. The sampling method was randomly classified. The Cochran formula was used to determine the sample size. In order to determine the effective indicators while studying the available sources and using the Porter model, as a basic model and after conducting the necessary studies and factor analysis, the conceptual model of the research was designed in form of three main criteria including environmental factors, intra-organizational factors and factors creating perceptual value as well as 9 sub-criteria. After conducting the necessary studies, preparing a researcher-made questionnaire and data factor analysis, the conceptual research model was designed and by conducting a field research and analyzing the results using student's t-test and Friedman test, the relationship between laminate flooring competitiveness with 3 criteria and 9 sub-criteria was examined. The reliability of the data was confirmed by Cronbach's alpha method. The mean of all studied indices was evaluated as moderate based on the results of descriptive statistics. Based on the results of the t-test, environmental factors, intra-organizational factors and factors creating perceptual value have a more than average role on competitiveness. Also, based on Friedman test, prioritization of indicators was obtained respectively based on environmental factors, factors creating perceptual value and intra-organizational factors. [ABSTRACT FROM AUTHOR]

This study aims to identify the expectations and preferences of consumers of home and office furniture using nonparametric tests. The statistical population consists of customers of the home and office wood furniture industry in Tehran and a stratified sampling method was used in this study. Cochran formula was used to determine the sample size. To determine the effective indicators, the researcher studied the available resources and the Van et al.'s model as the basic model and conducted a factor analysis to design the conceptual model of the research. Using a field research, the student t-test and Friedman test, she examined the relationship between consumer preferences and 5 factors and 17 subindices. Results: The reliability of the questionnaire was confirmed by the data obtained from 100 questionnaires using Cronbach's alpha. The results of descriptive statistics indicated that the mean of all the indices was at an average level. The minimum and maximum values and the standard deviation showed that there were no outliers. The results of inferential statistics in SPSS software indicated that the significance level for Kolmogorov-Smirnov test was greater than 5%, and all variables are assumed to be normally distributed. The results indicated a significant relationship between all indicators and consumer preferences regarding home and office furniture. The results of the one-sample t-test indicated that consumers consider corporate responsibility factors, product and vendor's characteristics and internal factors above average while they consider environmental and safety factors at the average level in the purchase of home and office furniture. The results of the Friedman test indicated the priorities as follows: vendor's characteristics, internal factors, corporate responsibility factors, product characteristics and safety and environmental characteristics. [ABSTRACT FROM AUTHOR]

Introduction In the pursuit of detecting the trend and the shift in trend in hydro-meteorological variables, various statistical methods have been developed and used over the years. Of the two methods commonly used (parametric and non-parametric), the non-parametric method has been favored over parametric methods. Long term trend analysis can reveal the beginning of the trend year, trend changes over time, and abrupt trend detection in a time-series. It is expected that the findings of this study will bring about more insights on understanding the regional hydrologic behavior over the last several decades in Iran. Methodology This paper analyzes the behavior of annual and seasonal temperatures, precipitation, and relative humidity. Datasets of 37 stations in Iran were analyzed from 1961 to 2010. The pre-whitening technique was used to eliminate the effect of the autocorrelation of data series. The Mann–Kendall (MK) test and the Sen's slope estimator were applied to quantify the significance of the trend and the magnitude of the trend at a 95% confidence level, respectively. The surface interpolation technique was used to prepare a spatial temperature, precipitation, and relative humidity data map over Iran from the point data measuring stations within the ArcGIS framework. For spatial distribution of trends in maps, contours are generated using an inverse-distance-weighted (IDW) algorithm.