Good Example Of Essay On Attributes Of A Data Set Represented Using Histograms

Program

A histogram provides one of the many ways of visually representing a data set’s distribution. The main difference between a histogram and other types of visual representations is that histograms do not retain all the elements of a data set. Instead, it gives a summary of discrete or continuous data on an interval scale. Statistically, the histogram demonstrates the essential features of data distribution in a more appropriate form. For one to construct a histogram, they first divide a data set into groups depending on the range of data values. The user then creates rectangles for each group with a width equal to the range of values and the height equal to the number of observations in the group. As such, the rectangles have different heights.
Since the histogram visually represents the distribution of data set, one can determine data attributes such as skewness, presence of outliers, or the normal distribution. Distribution of a data set may either be symmetrical or asymmetrical. In such a scenario, the columns in the histogram form a bell-shaped figure. A symmetric distribution is representative of a normal distribution while an asymmetric distribution is representative of a skewed distribution. For skewed distribution, the histogram has its bars concentrated on either the left or right side. As such, it is possible to identify the data set as either positively or negatively skewed.
In most cases during the construction of a histogram, the bars representing the groups have equal widths. In some other cases, the group intervals have different sizes. In such cases, it is important to select the width of the bars appropriately. The use of histograms usually extends to numerical values measured in intervals. As such, statisticians commonly use histograms for large data sets. That way, the histogram plays a significant role in identifying the gaps or unusual observations in the data.

References

Histograms. (2013, January 1). Retrieved January 29, 2015, from https://statistics.laerd.com/statistical-guides/understanding-histograms.php
Martinez, W., & Martinez, A. (2002). Computational statistics handbook with MATLAB. Boca Raton: Chapman & Hall/CRC.