A MULTIPLE LINEAR REGRESSION MODEL IS USED TO ANALYZE DATA FOR CENSUS TRACTS WITHIN THE CITY OF ST. LOUIS, FOR THE CITY AS A WHOLE, AND FOR THE COUNTY. THE PROPERTY CRIME CATEGORY IS THE SUM OF THE BURGLARY, AUTO THEFT, AND LARCENY CATEGORIES. AFTER REVIEWING THE WORK OF OTHERS IN THE FIELD OF ECONOMIC INFLUENCES ON CRIME, THE THEORETICAL BASIS FOR THIS WORK IS DESCRIBED IN DETAIL. CHARTS, TABLES, AND SAMPLE COMPUTER PRINTOUTS ILLUSTRATE THIS MATHEMATICAL DISCUSSION. VARIABLES USED INCLUDE REPORTED CRIMES PER 1,000 POPULATION, CRIME RATES PER 1,000 AFTER ADJUSTMENT FOR SYSTEMATIC NONREPORTING, MEDIAN FAMILY INCOME, MEAN WAGE OR SALARY INCOME PER EARNING FAMILY, MEDIAN YEARS OF SCHOOL COMPLETED, UNEMPLOYMENT RATES FOR MALES AND FEMALES, PERCENTAGE OF FAMILIES BELOW POVERTY LEVEL, RELATIVE POVERTY LEVEL, RACE, LENGTH OF TIME IN A RESIDENCE, MARITAL STATUS, AND NUMBER OF MALES AGED 18-24. GENERALLY, THE PARTIAL REGRESSION COEFFICIENTS FOR THE PERCENT OF FAMILIES BELOW POVERTY LEVEL, PERCENT OF MALES BETWEEN AGES 18 AND 24, PERCENT OF FAMILIES RESIDING IN THE SAME HOUSE AT LEAST 5 YEARS, RATE OF FEMALE UNEMPLOYMENT, AND MEDIAN YEARS OF SCHOOL PROVE MOST IMPORTANT IN DETERMINING LEVEL OF OFFENSES. HOWEVER, THE MEASURE OF YEARS OF SCHOOLING SHOWS A POSITIVE RELATIONSHIP AND FEMALE UNEMPLOYMENT A NEGATIVE RELATIONSHIP, WHICH IS CONTRARY TO THE HYPOTHESIS. A PARTIAL NEGATIVE RELATIONSHIP IS FOUND ALSO BETWEEN PROPERTY CRIME NUMBER OF POLICE AND PROBABILITY OF APPREHENSION. THE RELATIONSHIPS FOUND FOR THE VARIOUS STATISTICAL BREAKDOWNS ARE DISCUSSED IN DETAIL. NUMEROUS TABLES GIVE STATISTICAL DATA. A BIBLIOGRAPHY AND FURTHER STATISTICS ARE APPENDED. (GLR)