The formula for finding the mode in grouped data is given by:
$$ mode = l + \frac {f_1 - f_0}{2 f_1 - f_0 - f_2} X h $$
where,
l = the lower limit of the modal class,
$ f_1 $ = the frequency of the modal class, $ f_0 $ = the frequency of the class preceding the modal class, $ f_2 $ = the frequency of the class succeeding the modal class, h = class width.
There's already a good answer here; an excerpt:
"Now, observe that: $$ \frac{f_1 - f_0}{2f_1 - f_0 - f_2} + \frac{f_1 - f_2}{2f_1 - f_0 - f_2} = \frac{f_1 - f_0}{(f_1 - f_0) + (f_1 - f_2)} + \frac{f_1 - f_2}{(f_1 - f_0) + (f_1 - f_2)} = 1 $$ So if we want to divide an interval of width h into two pieces, where the ratio of sizes of those two pieces is $ (f_1 - f_0) : (f_1 - f_2) $, ), the first piece will have width $ \frac{f_1 - f_0}{2f_1 - f_0 - f_2} h $. This is what the formula for estimating the mode does. It splits the width of the modal bar into two pieces whose ratio of widths is $ (f_1 - f_0) : (f_1 - f_2) $, , and it says the mode is at the line separating those two pieces, that is, at a distance $ \frac{f_1 - f_0}{2f_1 - f_0 - f_2} h $, from the left edge of that bar, $ l $."
The answer does a very good job of explaining what the formula is, but it doesn't touch on:
why we'd expect the mode to be at the line separating the two pieces. Why can't the mode be somewhere else?
I understand that this is approximating, but why do we use this particular approximation?
Further, why do we use the differences between $ f_1 $ and $ f_0 $ & $ f_1 $ and $ f_2 $:
why do we care how much the frequency of the modal class is higher or lower than the frequencies of the classes preceding or succeeding it?