Some interactive econometric SOFTWAREs may meet the needs of economic researcher. However, they have their own shortcomings in generalizing econometric estimates and prediction models. This has made programming environment and its applications in economic researches more important. The R SOFTWARE, with its various applications, has established itself a very useful program among researchers. This paper demonstrates some of R' s applications and advantages for students and researchers who face problems and limitations with interactive computational SOFTWAREs. Being free of any expenses is one positive aspect among other features. Also through examples, some of its merits in econometrics and time series analysis are presented.

Researchers in different disciplines often face phenomena of random nature. Sometimes it is possible to use probability distributions to describe and predict such phenomena. Each distribution has a number of unknown parameters, whose values are estimated from data. In some problems, there are a few competing distributions for fitting to a data set. In this setup, selecting a suitable model based on some criteria is necessary. This article introduces facilities of R statistical SOFTWARE in performing the above steps. Application of the discussed methods is illustrated using a medical data set.

Network analysis is an advanced statistical and graphical method which visualizes the relationship between multiple variables. The purpose of this research is to describe the analysis of computational psychological networks. Psychological network analysis helps researchers find the most important variables and relationships in a complex system. The latest estimation tools included accuracy using Bootstrap method, the degree of stability of focal indices, linkage comparison in psychological networks, and estimated indices. In addition, two new statistical methods called stationary correlation coefficient and the bootstrapped difference test were presented to compare edge-weights difference and focal indices. The statistical population of the research included 368 (120 male and 248 female) students of Tehran universities in the academic year of 2019-20. Then the anxiety of participants was measured. Network analysis using R showed that nodes 3, 6 and 11 are the most important nodes and the relationships between nodes 12-18 and 17-18 had the strongest positive relationships. Bootstrap method showed that the parameters and focal indicators of the network provide the correct estimation. The practical and interpretive steps of the mentioned theoretical foundations were presented in practical formats with anxiety data using R statistical SOFTWARE. The design of this article is based on theoretical and practical implications.

Drought is one of the main hazards related to weather that can affect all aspects of life. In order to monitor and manage droughts using relevant indicators, six synoptic stations were selected in South Khorasan province, corresponding to the cities of Birjand, Qain, Nehbandan, Ferdous, Tabas and Beshravieh. Then the required data was collected and analyzed. According to the review of the available data, the statistical period of 31 years (1990-2020 AD) was chosen as the statistical period of the research. R SOFTWARE is one of the SOFTWARE that is very useful for statistical analysis and has libraries for calculations in different basins. In this research, SDI and RunDS drought indices were calculated using the Drought library for each of the stations. Also, in order to calculate RAI and PNPI drought indices for each station, coding was done. The results showed that according to the SDI index, the driest month and year during the statistical period are October and 2008, respectively. Also, according to the SPI index, Tabas city is in the extreme drought category and has experienced the most drought compared to other cities. In the case of RunDS, Ferdous city had the longest duration of drought and Tabas had the highest intensity of drought. Based on all indicators, Tabas city was recognized as the driest city due to 53 months of drought. Also, based on the results obtained from the R SOFTWARE, the SDI index estimates results closer to reality than other indices in long-term time scales.

Background: The correlation coefficient is a statistical measure that measures the degree of correlation between two variables and takes values between -1 and +1, which indicates the strength and direction of the linear relationship between two variables. Correlation coefficients play a significant role in medical science studies. These coefficients help researchers to identify and measure the relationship between different clinical variables and health outcomes. Description of the Article: Considering the importance of calculating correlation coefficients in medical research, the purpose of this paper is to introduce various types of correlation coefficients, simple and applied statistical concepts and, methods to investigate the relationship between variables according to their nature and how to calculate them. Types of commonly used correlation coefficients, including Pearson, Spearman, Kendall, Phi, V Kramer, Summers Delta, Gamma, agreement coefficient and, Landa correlation coefficient will be analyzed using SPSS and R SOFTWARE. Also, the conditions of using each of the correlation coefficients will be discussed according to the different assumptions and the unique interpretation of each of the coefficients. Finally, examples of the calculation and interpretation of each of the correlation coefficients in medical sciences are provided.Conclusion: Correlation is the most widely used statistical measure to evaluate the relationships between variables. However, it should be used with caution. Otherwise, it can lead to erroneous interpretations and results.

Introduction: Pharmaceutical companies as well as food and cosmetics manufacturers are legally required to provide a shelf-life label on their products packaging as part of their stability study report. There are different recommended SOFTWARE like R SOFTWARE package and SAS which can perform as shelf-life estimating tools for analyzing the data achieved by the stability testing of drugs and vaccines. Methods: Recombinant hepatitis B surface antigen vaccine (Pasteur Institute of Iran) was used as a sample for the entire quality control assays according to Pharmacopeia and NIH (National Institute of Health) procedures. For the stability study, full test examinations were done and R SOFTWARE package was applied to estimate the shelf-life. Results: The results of R SOFTWARE indicated a variety of statistical information which makes the data interpretation more intelligible and apprehensible. Conclusion: Based on our results and experience, the best way to obtain a shelf-life or the expiration date is to calculate it manually; however, using SOFTWARE such as R can increase the accuracy of the results.

In recent decade, there has been a substantial reduction in the water level of Lake Urmia. Understanding the underlying causes and pivotal moments of these changes, always have importance in environmental and water resources studies. This study aims to analyze the water level fluctuation, the climatic parameters trends and their interrelationship in Lake Urmia Basin. The data were collected from Urmia airport synoptic station and over 50 years, from 1973 to 2022 on a monthly and annual scale. For trend analysis, the Mann-Kendall, seasonal Mann-Kendall, and correlated seasonal Mann-Kendall tests and for change detection, Standard Normal Homogeneity Test (SNHT), Pettitt's test, the Buishand range test, and U Buishand test, were used. The results of study showed that, the maximum and average temperatures time series showing an increasing trend and the minimum relative humidity demonstrating a decreasing trend. Also, a significant decreasing trend was observed in the lake's water level during this period.  Change point tests identified the years 1999 to 2001 as the turning point for the lake's water level, and for other parameters, change points were in the 1990s on both annual and seasonal scales. Furthermore, the lake's water level exhibited different behaviors before and after the change points. The results of this study, indicates a major climate change in the Lake Urmia catchment since year 2000, resulting water level decrease and dry up in this lake.