Common Graphs in Statistics
Statistics is ruled by collecting data samples and putting them in graphs to make the data easier to read. There are numerous ways data can be organized into a graph, depending on the variables used in the experiment or those collected during a survey.
Choosing which kind of graph to use is dependent on the aforementioned variables as well as really what makes the graph easy to read.
While some graphs might be able to contain all the information you wish to plot, some of them might not work very well simply because they don't display the information in an easy to understand format.
It's important to learn the different types of graphs, so that you're able to select the one that will best displays information.
Common Statistical Graphs
Pie chart or circle graph: This one is good for showing your data as percentages as a whole. Each slice of the "pie" represents one category and you can conveniently pull one out of the circle to emphasize that particular category.
Bar graph (Pareto diagram): This form of graph is typically used to compare the frequency, or number of occurences, in each category. It uses vertical or horizontal bars, usually organized by frequency. The bar chart is two-dimensional with an X-axis and Y-axis.
Histograms: A histogram is similar to a bar chart, but takes the range of values into account. That means the bars cannot be rearranged by the number of occurences. This form of graph is commonly used for calculating probabilities and any application where you want to emphasize the frequency of occurences in quantitive data.
Stem and Leaf Plots: If your teacher has ever made a chart showing how many people got certain letter grades on a test, you've probably seen one of these. The class of values, like test scores, are usually placed in the left column, the "stem", and the frequency, the "leaf", is placed in the right. If you are breaking down test scores for more than one period, you can arrange the frequency of each class in a horizontal row for each period.
Dot plots: Dot plots are like a blend of histograms and stem and leaf plots. The frequency of each category is shown as a vertical column of dots. In most dot plots, each dot represents one occurrence.
Scatter plots: This type of graph makes use of a two-dimensional chart with X-axis and Y-axis to plot two variables in a set of data. It is designed to establish the relationship between the two variables, which is called the correlation. It can be used to show positive correlation, in which an increase in one value causes an increase in the other. This type of graph can show negative correlation, in which an increase of one value causes a decrease an another. It can also show high correlation, in which the relationship between the two values nearly causes the scatter plot to show a straight line, low correlation, in which the values appear a little more spread out, or it might show no correlation at all.
Time series graphs: This type of graph is designed to show trends in data collected over a period of time. The data is usually displayed with the time increments along the X-axis and the values along the Y-axis. It is useful for tracking population trends in a certain area, weather patterns over months and years and several other applications where you want to track data over a long period of time.
Using Graphs For Statistics
Graphs are useful for comparing values in your data and making comparisons that support, or maybe disprove, that point you want to make. You can use them as part of a sales presentation, educate others about the data involved in your work or just for personal reference while you continue to build on previous work. They can also let you know when you need to scrap something and start all over. So learning how to create and use them can be a big help when working with statistics.