Correlation

Grades represent one of the most common sources of evidence of student achievement in classrooms, though their relationship with test scores has remained understudied, particularly in settings such as in Iran, where English is taught as a foreign language. The purpose of this study was to investigate the relationship between graded and tested achievement with respect to gender and proficiency level differences. Teacher-assigned grades and standardized achievement test scores of 693 Iranian learners of English taught by 15 teachers were examined. Primary analyses focused on the validity of teacher grades and the subsequent Pearson correlation coefficients revealed that grades associated positively with externally-validated test scores obtained from reliable tests, an indication of the validity of teacher grading. Additionally, the results of independent-samples t-tests showed that female students outperformed male students on achievement tests, but with fluctuations across proficiency levels. Higher proficiency levels gave male participants an advantage over female participants in achievement tests. Moreover, male teachers were found to grade female participants more accurately than their female counterparts. Implications are discussed for informing teachers about the validation of their grading practices, as well as for teacher education programs and teachers’ professional development.

Disaster Management and current approaches in this field in one hand only has focused to physical vulnerabilities and in the other hand has included consequential action to reduce vulnerability and improve physical preparation as well as resistance institutional insignificant during the disaster. Therefore, these approaches usually have ignored the capabilities and capacities of residents to reduce vulnerabilities and consequently losses and damage. While recent approaches have entered, the field of disaster management emphasized that at first vulnerability is beyond the physical vulnerabilities and second vulnerabilities have an inverse relationship with the resident’s capacity in the face of disaster. So, community-based disaster risk management need to recognize indicators of vulnerability and community capacity and its relationship is essential. Accordingly, in the first step, the indicators of community capacity and community vulnerability are provided and in the second step based on these indicators, community capacity and vulnerability have been assessed. The assessment of community characters is based on GIS capabilities, spatial analysis tools and SPSS and correlation regression is used for analyzing the relationship of the variables. The results and findings of this research indicate that the vulnerability of urban areas is not only influenced by physical factors, but also social and organizational factors like community organizing and community educating have affected strongly the vulnerability.

Assessment literacy refers to the knowledge teachers have about definitions of testing and the employment of this knowledge to classroom practices. This study inspected the extent to which high school teachers of English, mathematics, science, and social studies utilize assessment literacy and instructional improvement practices in their classrooms and the probable relationship between these two factors. To this end, ninety-seven teachers from sixty high schools across Zanjan province in Iran were selected based on convenient sampling. The instrument used was a 32-item questionnaire designed by researchers and validated by experts. A confirmatory factor analysis (CFA) was also conducted in order to validate the factor structure of the questionnaire. The results showed a strong positive relationship between assessment literacy and instructional improvement practices in all four subject areas through correlations. This suggests that showing an understanding of assessment literacy results in a greater understanding of instructional improvement in the classroom. Moreover, a one-way ANOVA was performed in order to determine if there is a significant difference in the use of assessment literacy practices and instructional improvement among different subject areas. The data revealed no statistically significant differences between neither assessment literacy nor instructional improvement scores by subject area. The study can be beneficial to school districts and teachers since the review of existing teaching practices and an increase in ongoing professional development in assessment literacy theories and practices may improve instructional improvement in all subject areas.

In every country, airports are among the most important air transport systems in that country. When an aircraft flies from one airport to another, it creates a graph that can be completed with information about each flight, such as the number of flights per path, the number of passengers, traffic load, and so on. In the present paper, the airports of Iran and the domestic flights are considered as a network and the structure of the network is analyzed, and then the measures of complex networks such as degree distribution, shortest path length, analysis of centralities, clustering coefficient and their correlation and the way these centralities behave are examined. This analysis shows the Iranian Airport Network (IAN) that has a degree distribution described by the power function. The average path length in this network is 1.9, and the average clustering coefficient is 0.69, which meets the characteristics of a small-world network and is also considered an example of a disassortative network. The purpose of this research is to investigate the network of airports in Iran, which is ultimately important for the expansion of airports, and also to identify the important points of airports.

Abstract Negative binomial regression model (NBR) is a popular approach for modeling overdispersed count data with covariates. Several parameterizations have been performed for NBR, and the two well-known models, negative binomial-1 regression model (NBR-1) and negative binomial-2 regression model (NBR-2), have been applied. Another parameterization of NBR is negative binomial-P regression model (NBR-P), which has an additional parameter and the ability to nest both NBR-1 and NBR-2. This paper introduces several forms of bivariate negative binomial regression model (BNBR) which can be fitted to bivariate count data with covariates. The main advantages of having several forms of BNBR are that they are nested and allow likelihood ratio test to be performed for choosing the best model, they have flexible forms of mean-variance relationship, they can be fitted to bivariate count data with positive, zero or negative correlations, and they allow overdispersion of the two dependent variables. Applications of several forms of BNBR are illustrated on two sets of count data; Australian health care and Malaysian motor insurance.