Ogive vs Cumulative Relative Frequency

An ogive plots running totals instead of the count inside each bin, so it answers questions of the form how much of the data sits at or below this value. For example, with 40 test scores, if 30 of them are 80 or lower the graph passes through the point $(80, 0.75)$, since $30 / 40 = 0.75$. The curve never goes down and finishes at $1$, that is, 100 percent, which makes it a direct way to read percentiles off a graph. The AP Statistics course framework does not name ogives, so you will meet them more often in college courses and older textbooks.

Cumulative relative frequency tells you what fraction of the data you have accounted for by the time you reach a certain point, so it rises to 1 as you work through the ordered categories. You compute it as $\frac{\text{cumulative count}}{n}$, where $n$ is the total number of observations. In a class of 40 students, if 10 scored below 70 and another 14 scored in the 70s, the cumulative count through the 70s is 24 and the cumulative relative frequency is $24/40 = 0.60$. That 0.60 is also a statement about position: the top of the 70s band sits at roughly the 60th percentile.