Final answer:
Yusuf is most likely finding the mean of his data set, which requires summing all values and dividing by the number of those values. The mean is a measure of the central tendency, commonly used unless skewed by outliers where the median might be more appropriate.
Step-by-step explanation:
When Yusuf adds all the values in his data set together and then divides by the number of values in his set, he is most likely finding the mean of the data set. The mean is also commonly known as the average and it is a measure of the center of a data set. To calculate the mean, you sum all the numerical values and divide by the number of values present. This process is distinct from finding the median, which is the middle value when a data set is ordered, the mode, which is the most frequently occurring value(s), or the range, which is the difference between the highest and lowest values in the data set.
Examples of calculating the mean include summing the weights of a group of people and dividing by the number of people to get the average weight, or adding up the values of houses on a block and dividing by the number of houses to find the average house value. In the presence of extreme values or outliers, the median is usually a more accurate measure of the center because it is less affected by the skewness of the data.
In a symmetrical distribution, the mean, median, and mode will be equal, highlighting the relation between these measures of central tendency. However, when data is skewed, the mean will reflect that skewing more than the median or mode.