Comparing Different Types of Graphs: Advantages and Disadvantages, Study notes of Advanced Data Analysis

Download Comparing Different Types of Graphs: Advantages and Disadvantages and more Study notes Advanced Data Analysis in PDF only on Docsity! (R 2-12) WHA Quality Center Source: http://math.youngzones.org/stat_graph.html Using Graphs to Display Data Each type of graph has its advantages and disadvantages: Graph Advantages Disadvantages Pictograph A pictograph uses an icon to represent a quantity of data values in order to decrease the size of the graph. A key must be used to explain the icon.  Easy to read  Visually appealing  Handles large data sets easily using keyed icons  Hard to quantify partial icons  Icons must be of consistent size  Best for only 2-6 categories  Very simplistic Line plot A line plot can be used as an initial record of discrete data values. The range determines a number line which is then plotted with X's for each data value.  Quick analysis of data  Shows range, minimum & maximum, gaps & clusters, and outliers easily  Exact values retained  Not as visually appealing  Best for under 50 data values  Needs small range of data Pie chart A pie chart displays data as a percentage of the whole. Each pie section should have a label and percentage. A total data number should be included.  Visually appealing  Shows percent of total for each category  No exact numerical data  Hard to compare 2 data sets  "Other" category can be a problem  Total unknown unless specified  Best for 3 to 7 categories  Use only with discrete data Map chart A map chart displays data by shading sections of a map, and must include a key. A total data number should be included.  Good visual appeal  Overall trends show well  Needs limited categories  No exact numerical values  Color key can skew visual interpretation Histogram A histogram displays continuous data in ordered columns. Categories are of continuous measure such as time, inches, temperature, etc.  Visually strong  Can compare to normal curve  Usually vertical axis is a frequency count of items falling into each category  Cannot read exact values because data is grouped into categories  More difficult to compare two data sets  Use only with continuous data