Julio is a social worker working in a treatment foster care agency. His job is to conduct intake assessments and place children with the best matching foster care family. Recently, Julio was tasked with researching the success rate of foster care families and the children's success within the system. He created a study to be completed with the families connected with his agency. Julio finished interviewing all the families and was ready to compile his data. He interviewed 55 families total and 45 foster care children. He asked them to answer questions in several different areas, including the average length of stay for the children placed with them, family cohesiveness, mental and physical health concerns regarding the foster children, and recidivism of the children once they left the foster home and returned to their own families. Julio was able to collect enough data to determine the success rate of the agency.

How might Julio compile the raw data to better understand what information he has gathered?

If Julio creates a bell curve and the curve is skewed to right, what conclusion can he make about the success rate of the agency?

Julio organizes his data in such a way that he can see common reasons why children are not successful in the agency. How can the mode of his dataset help him create a solution to this issue?

How can the mean, median, and mode help Julio better understand the raw data? What might be a drawback of using each of these measures of central tendency?