Empirical Research On Statistical Diagnosis Of Data Quality

Social and economic development requires real,accurate and comprehensive statistical data.The quality of statistical data is a mirror of the development of various industries.The quality of the quality determines the clarity of the mirror.The quality of statistical data in the medical industry is especially important,and accurate and effective data analysis is about the immediate interests of patients.In particular,the comprehensiveness and complexity of hospitalization expenses are the part of patients who demand the highest quality of their data.In order to understand the factors of the complex medical expenses data and the reasons that affect the quality of its statistical data,this study selected chronic kidney disease with high medical expenses as the research object,diagnosed its data components,and found out the quality of statistical data.The problem is to avoid conflicts between doctors and patients,improve the quality of hospital services,and promote the harmonious coexistence between hospitals and patients.In view of the fact that the actual data does not meet the established assumptions,making the analysis results unreliable,more and more statisticians diagnose the statistical data of our country through mathematical models and mathematical methods.In this context,this paper makes a reasonable statistical diagnosis based on the data of hospitalization costs of chronic kidney disease.Based on the original data and actual status of the disease patients,the paper focuses on the theoretical basis of data quality control,analyzes the factors affecting the hospitalization cost of chronic kidney disease,and uses the method of independent variable selection to screen the influencing factors and obtain the SAS operation.The optimal subset is established and the regression model is established.Then,based on the theoretical basis of data deletion model and local impact analysis,SPSS is used to judge abnormal points,and R software is used for multi-dimensional analysis of data parameter estimation and statistical inference.Finally,by example The data is compared with the goodness of model fitting,and the data transformation process is carried out to obtain the conclusion that the data quality is improved.The purpose of the research is to find out the impact of the data points on the regression model,and to find the entry point to improve the model optimization,toexplore the essence of improving the quality of the data through the problems reflected by the actual data,and to provide the cost of treatment for the chronic kidney disease in reality.policy suggestion.