2.1. Histograms and Frequency Distributions http://www.ck12.org
If the distribution is symmetric and mound shaped, then the ogive plot will look just like the shape of one half of
such an arch.
Lesson Summary
Afrequency tableis useful to organize data into classes according to the number of occurrences in each class, or
frequency.Relative frequencyshows the percentage of data in each class. A graphical representation of a frequency
table (either actual or relative frequencies) that uses bins to show the amount in each class is called ahistogram.
Though it looks very similar, a bar graph is only used for categorical variables. Afrequency polygonis created
by plotting the midpoints of each bin at their frequencies and connecting the points with line segments. Frequency
polygons are useful for viewing the overall shape of a distribution of data as well as comparing multiple data sets.
For any distribution of data you should always be able to describe theshape, center, and spread. Data that is
mound shapedcan be classified as eithersymmetricorskewed.Distributions that areskewed lefthave the bulk
of the data concentrated on the higher end of the distribution and the lower end ortailof the distribution is spread
out to the left. Askewed rightdistribution has a large portion of the data concentrated in the lower values of the
variable with a tail spread out to the right. Anogive plot,or relative cumulative frequency plot shows how the data
accumulates across the different values of the variable.
Points to Consider
- What characteristics of a data set make it easier or harder to represent it using frequency tables, histograms,
or frequency polygons? - What characteristics of a data set make representing it using frequency tables, histograms, frequency polygons,
or ogives more or less useful?