Data visualization is usually the graphical representation of data and information by employing graphs, maps, and charts. The process of data visualization enables an individual to study the patterns, trends, and outliers in data. We choose the Home value (from Zillow), which we were supposed to analyze using different visual representations. To ensure better analysis of large data sets like the one provided in excel, techniques such as drawing bar graphs and scatter charts were used. Scatter charts and bar graphs, in most cases, can be used to visualize large data sets. The two visualization charts were used because of the various and many advantages they bring along.
A scatter chat is usually a graph that employs dot to represent different values of data. In most cases, this type of chart is used to show the relationship that exists between variables. Like in our case, we can be able to compare the different cities. Also, Bar graphs are necessary visualization charts because they make it easier to understand various data sets.
In conclusion, scatter visualization charts are fundamental as they help show the correlation between the two variables. The relationship being showed using the technique always is between cause and an effect or two causes. It can be negative, positive, or, in some cases, no relationship can be experienced. Usually, in this type of visualization chart, the first variable is, in most cases, independent while the second variable depends on the first one. To ensure a better analysis of the correlation pattern, an individual can change the independent variable and then monitor the dependent variable’s changes. Scatter visualization charts usually have two independent variables (Wischenbart and Rüdiger,2012).
References.
Wischenbart and Rüdiger (2012). Publishing Statistics (PDF). IPA Global.
