Final answer:
A histogram is used to represent the distribution of data, and in this case, it represents the graduation rates for a sample of colleges and universities. The shape, central tendency, and variability of the histogram can provide insights into the data. Relative frequencies help understand the proportions of different graduation rate ranges.
Step-by-step explanation:
A histogram is a graph that represents the distribution of data. In this case, the histogram represents the graduation rates for a random sample of 60 colleges and universities in the United States. The shape of the histogram can help us determine the distribution shape of the data. If the histogram is approximately symmetric, it suggests a normal distribution; if it is skewed to the right or left, it suggests a skewed distribution.
The central tendency of the data can be estimated by finding the mean or the median. In this case, we can estimate the mean graduation rate by finding the center of the histogram. The variability of the data can be estimated by examining the spread of the histogram.
The observed graduation rates in the histogram show that most colleges and universities have graduation rates between 60% and 80%. There is also a smaller group of institutions with graduation rates below 60%. The pattern in the histogram suggests that there may be a higher number of colleges and universities with moderate to high graduation rates, and a smaller number with low graduation rates.
Using relative frequencies in understanding the data helps us compare the proportions of different graduation rate ranges. It allows us to see the distribution of graduation rates relative to the total number of colleges and universities in the sample. Factors influencing graduation rates in higher education institutions can include the quality of education, student demographics, resources, and support services provided by the institutions.