کاربرد نرم افزارهای آماری در مطالعات کمی بازاریابی ورزشی

With the increasing growth of scientific research in the field of physical education and sports science, the use of statistical software has become obvious. In fact, choosing a type of statistical software according to its features and considering ethical issues may require payment. Today, many statistical softwares are provided for free. Some are in the category of general software that has the ability to perform a wide range of statistical analysis, and on the other hand, small and limited software that has been developed to perform a specific analysis. Some of these softwares have been created only for calculations and have the role of a software calculator, while others are in the form of plugins and can not be run independently. Also, some software has been developed only for a specific research group such as agriculture, social sciences, physiology, biomechanics, etc. This section introduces general statistical software that has the ability to perform a wide range of statistical analysis. The purpose of this study is to review free statistical software in physical education and sports sciences, which are: SPSS ،Lisrel ،Amos ،Pls ،EQS ،Jasp ،Jamovi ، MaxStat ،PSPP ،R ،Stata ،S-Plus ،Excel ،Statistician ،Minitab ،Atlas ،Xlstat ، Origin،Systat ,Past. Statistical software has special features depending on their nature. Accordingly, the choice of a free statistical software depends to a large extent on the capabilities of the statistical test desired by the software by the software, but in commercial versions due to the breadth and variety of commands and statistical commands in the software, this factor is a limited factor. Is not considered a supplier. One of the most important and essential things in choosing a statistical software is the user interface of that software. In fact, the user interface of & statistical softwares is considered graphically or selectively oriented. But the user interface of R statistical software is textual and commands are given to the software through the programming language. In this regard, learning and understanding software with a graphical user interface is possible in a few hours, but in order to learn R software, you need to spend more time. Some of these statistical softwares such as R and PSPP have help and training packages that do not help the user to learn the basics of the software. Also, many softwares have online guides and educational pages in cyberspace, such as statistical softwares R, PSPP, Vista and OpenStat (Hakimi, 2014). Choosing a statistical package by consumers is often a difficult process and it is necessary to compare different products in order to select the most appropriate one, and this selection should be done based on clear criteria and in accordance with the goals set by researchers (Lina et al. , 2021). In this regard, in order to compare free statistical software, after downloading and installing this software from publishing sites, using the guide in the software as well as sample data, their efficiency and ability in different commands were compared. In order to evaluate the use of statistical software, the number of articles published in ScienceDirect database was measured. Figure 1 shows the number of articles published in 2020 that statistical software was used to analyze the data. Based on these results, SPSS software has the highest usage and MINITAB and SYSTAT software are in the next ranks. The results showed that all these softwares are legally free and without payment and all the results extracted from them can be published. Also Lisrel, Amos, Pls, EQS software are most used in the field of structural equation modeling. In this study, several software packages with their capabilities, compatibility, usefulness and limitations are explained, so what is certain is that researchers use different statistical packages to analyze similar data. Each packet has basic statistical capabilities that can be used, but each packet has its own advantages and disadvantages for using different types of data analysis. Many statistical software developers try to make the graphical user interface capabilities more user-friendly. According to the results, SPSS and Minitab are still the most popular tools for statistical data analysis, especially for those with low statistical or mathematical competencies. The results show that free and open source statistical software have good capabilities, but how they can be used in more advanced ways is questionable. All statistical software has almost the same results (the number of decimals or some decimals may vary at best), although they follow different algorithms in each case. In addition, more information is provided in each software than in other packages. Therefore, according to the need, users should choose their software carefully. When processing and analyzing data, it is important to choose the appropriate statistical method to obtain correct decisions and & interpretations. Underestimating the importance of statistical methods and proper organization of relevant experiments can lead to incorrect scientific results.On the other hand, the large number of software packages and the fact that they offer similar or relatively identical opportunities suggest a complex choice that often cannot be made effectively due to the lack of a benchmarking system. Conducting studies such as the present study can help researchers select software that facilitates their work as much as possible in achieving the stated research goal. The choice of statistical software packages for learning should be based on the suitability of the software for all the analyzes that the researcher may want to analyze. Therefore, it is recommended to select at least two softwares to provide a broader and stronger learning analysis of the research. Finally, the researcher's opinion, after analyzing the field data to a great extent, is that statistical software has made a significant contribution to humanities research, especially in the field of demographic and data analysis. This was achieved by using a scientific approach to solve fundamental problems in research that is data analysis. Although some other factors such as literature review, methodology and findings have affected the quality of research work, but it is quite clear that the impact of statistical software packages on research analysis and findings can not be estimated.