{"title":"利用虚拟变量评估沙特阿拉伯1979-2011年降水回归模型","authors":"Manahil Eltayeb, Sulafa Hag-elsafi","doi":"10.35516/hum.v50i3.5404","DOIUrl":null,"url":null,"abstract":"Objectives: This study aims to analyze rainfall in Saudi Arabia by designing models based on data from 20 stations across the Kingdom from 1979 to 2011. \nMethods: The analysis employed a multiple linear regression model with rainfall as the dependent variable and annual quarters as the independent variables. Dummy variables were utilized in the analysis. The regression model provided valuable insights into the impact of rainfall rates in different quarters across Saudi Arabia. Monthly data was collected from each region of the Kingdom during the study period and categorized into five groups based on average rainfall: Group 1 (5-15 mm), Group 2 (15-25 mm), Group 3 (25-35 mm), Group 4 (35-45 mm), and Group 5 (45-70 mm). Each group was represented by a separate regression model. To reduce the number of dummy variables in the model, the monthly data was converted to quarterly data. \nResults: A significant finding of this study is that all models were statistically significant, indicating that rainfall distribution is influenced by the annual quarters. Furthermore, it was observed that the average rainfall in most quarters across different regions was statistically significant, except for the fourth quarter in Group 5 and the third quarter in Groups 1, 2, and 4. \nConclusions: The inclusion of dummy variables as independent variables in the multiple linear regression model proved to be a novel and effective approach for analyzing rainfall time series. The results can serve as a foundation for future studies, enabling prediction and informed decision-making based on the findings.","PeriodicalId":35252,"journal":{"name":"Dirasat: Human and Social Sciences","volume":"6 4 1","pages":""},"PeriodicalIF":0.0000,"publicationDate":"2023-05-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":"0","resultStr":"{\"title\":\"Assessment of Regression Model for Rainfall in Saudi Arabia (1979-2011) Using Dummy Variables\",\"authors\":\"Manahil Eltayeb, Sulafa Hag-elsafi\",\"doi\":\"10.35516/hum.v50i3.5404\",\"DOIUrl\":null,\"url\":null,\"abstract\":\"Objectives: This study aims to analyze rainfall in Saudi Arabia by designing models based on data from 20 stations across the Kingdom from 1979 to 2011. \\nMethods: The analysis employed a multiple linear regression model with rainfall as the dependent variable and annual quarters as the independent variables. Dummy variables were utilized in the analysis. The regression model provided valuable insights into the impact of rainfall rates in different quarters across Saudi Arabia. Monthly data was collected from each region of the Kingdom during the study period and categorized into five groups based on average rainfall: Group 1 (5-15 mm), Group 2 (15-25 mm), Group 3 (25-35 mm), Group 4 (35-45 mm), and Group 5 (45-70 mm). Each group was represented by a separate regression model. To reduce the number of dummy variables in the model, the monthly data was converted to quarterly data. \\nResults: A significant finding of this study is that all models were statistically significant, indicating that rainfall distribution is influenced by the annual quarters. Furthermore, it was observed that the average rainfall in most quarters across different regions was statistically significant, except for the fourth quarter in Group 5 and the third quarter in Groups 1, 2, and 4. \\nConclusions: The inclusion of dummy variables as independent variables in the multiple linear regression model proved to be a novel and effective approach for analyzing rainfall time series. The results can serve as a foundation for future studies, enabling prediction and informed decision-making based on the findings.\",\"PeriodicalId\":35252,\"journal\":{\"name\":\"Dirasat: Human and Social Sciences\",\"volume\":\"6 4 1\",\"pages\":\"\"},\"PeriodicalIF\":0.0000,\"publicationDate\":\"2023-05-30\",\"publicationTypes\":\"Journal Article\",\"fieldsOfStudy\":null,\"isOpenAccess\":false,\"openAccessPdf\":\"\",\"citationCount\":\"0\",\"resultStr\":null,\"platform\":\"Semanticscholar\",\"paperid\":null,\"PeriodicalName\":\"Dirasat: Human and Social Sciences\",\"FirstCategoryId\":\"1085\",\"ListUrlMain\":\"https://doi.org/10.35516/hum.v50i3.5404\",\"RegionNum\":0,\"RegionCategory\":null,\"ArticlePicture\":[],\"TitleCN\":null,\"AbstractTextCN\":null,\"PMCID\":null,\"EPubDate\":\"\",\"PubModel\":\"\",\"JCR\":\"Q4\",\"JCRName\":\"Social Sciences\",\"Score\":null,\"Total\":0}","platform":"Semanticscholar","paperid":null,"PeriodicalName":"Dirasat: Human and Social Sciences","FirstCategoryId":"1085","ListUrlMain":"https://doi.org/10.35516/hum.v50i3.5404","RegionNum":0,"RegionCategory":null,"ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":null,"EPubDate":"","PubModel":"","JCR":"Q4","JCRName":"Social Sciences","Score":null,"Total":0}
Assessment of Regression Model for Rainfall in Saudi Arabia (1979-2011) Using Dummy Variables
Objectives: This study aims to analyze rainfall in Saudi Arabia by designing models based on data from 20 stations across the Kingdom from 1979 to 2011.
Methods: The analysis employed a multiple linear regression model with rainfall as the dependent variable and annual quarters as the independent variables. Dummy variables were utilized in the analysis. The regression model provided valuable insights into the impact of rainfall rates in different quarters across Saudi Arabia. Monthly data was collected from each region of the Kingdom during the study period and categorized into five groups based on average rainfall: Group 1 (5-15 mm), Group 2 (15-25 mm), Group 3 (25-35 mm), Group 4 (35-45 mm), and Group 5 (45-70 mm). Each group was represented by a separate regression model. To reduce the number of dummy variables in the model, the monthly data was converted to quarterly data.
Results: A significant finding of this study is that all models were statistically significant, indicating that rainfall distribution is influenced by the annual quarters. Furthermore, it was observed that the average rainfall in most quarters across different regions was statistically significant, except for the fourth quarter in Group 5 and the third quarter in Groups 1, 2, and 4.
Conclusions: The inclusion of dummy variables as independent variables in the multiple linear regression model proved to be a novel and effective approach for analyzing rainfall time series. The results can serve as a foundation for future studies, enabling prediction and informed decision-making based on the findings.
期刊介绍:
Dirasat is an international peer-refereed research journal published in seven specialized series by the Deanship of Academic Research, University of Jordan. Issues of Dirasat: Human and Social Sciences are published tri-annually. Articles submitted are reviewed according to the highest standards by scientists specialized in their fields. The articles are written in Arabic or English.