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The study dealt with the use of one of the important statistical techniques, namely regression analysis in determining the factors related to the school dropout. Two variable selecting methods were used, which are the method of all possible regressions and the method of stepwise regression. The two methods were applied to the data collected about the dropout of students of primary schools in the capital, Baghdad. The study reached statistically significant results that the frequent failure of study, poor living, changing family housing, poor security, and bad relationship between teachers and students are factors that increase school dropout. A multiple linear regression model was constructed that quantifies the effect of each factor on the number of students who drop out, where all parameter values in the estimated model were positive. The most important result is that the use of the regression analysis technique has given results that are closely compatible with the results of many descriptive studies that dealt with the causes and factors that contribute to the spread of this phenomenon in society. corresponding author 2020 Mathematics Subject Classification. 62-08.

USE OF REGRESSION ANALYSIS METHODS TO DETERMINE FACTORS RELATED TO SCHOOL DROPOUT (AN APPLIED STUDY OF A SAMPLE OF PRIMARY SCHOOLS IN BAGHDAD)