A frequency distribution is a tabular or graphical presentation of data summarized into a comparatively small number of classes or intervals (also called ranges or bins). The intervals are mutually exclusive because each observation can fall into only one interval. Our selection about the number of intervals varies according to the length or basic shape of the data set.
When you are going to summarize and analyze large amounts of data, the frequency distributions can be a good choice to apply. Further, the frequency distributions can work with all types of measurement scales. Since frequency distributions are based on the number of occurrence of similar observations, so frequency distributions can be used for both quantitative and qualitative data.
A simple procedure for constructing a frequency distribution is as under:
If we divide absolute frequency by the total number of observations, we simply get the percentage of relative frequency. By successively adding the relative frequency at each interval is termed as a cumulative relative frequency.
How have equities rewarded investors in different countries in the long run? To answer this question, we could examine the average annual returns directly. The worth of a nominal level of return depends on changes in the purchasing power of money, however, and internationally there have been a variety of experiences with price inflation. It is preferable, therefore, to compare the average real or inflation-adjusted returns earned by investors in different countries. Dimson, Marsh, and Staunton (2011) presented authoritative evidence on asset returns in 19 countries for the 111 years 1900–2010.
Our calculator shows their findings for average inflation-adjusted returns. Summarize data using frequency distributions (when no. of intervals = 5) for the average real equity returns.
Because the range is the difference between the maximum and minimum returns, it can reflect extremely large or small outcomes that may not be representative of the distribution.