53. Star plots

http://stratochem.com/?attachment_id=371

A star plot is a radar chart that display multivariate data in a 2D chart or several quantitative variables that start from the same point. In this example you can see that there are four distinguishable spoke that is proportional to the magnitude of the variable it is representing. This gives it its star-like appearance, but the function of a map like this is handy when observers want to know where the clusters are, which is most similar or dissimilar points, and if there are any outliers. You can compare the red line with the blue to see how they compare and contrast.

52. Correlation matrix

http://www.emeraldinsight.com/journals.htm?articleid=1515237

Correlation Matrix is a table that display the correlation coefficients in several markets in various time frames. To put it simply, it gives the correlation between all pairs of data sets. This is an example of an industrial marketing team organizing their data in a model that helps them visualize the correlation for their study variables.

51. Similarity matrix

http://tomcat.esat.kuleuven.be/txtgate/tutorial.jsp

A similarity matrix is a matrix of values plotted on this graph measure the similarity between two data points. The purposes of this is to find clusters in data points and align DNA sequences. In this example, the data analyze the relationship between human genes and how they correlate to one another. f you look at the similarity color legend, the more red it is, the greater the difference.

50. Stem and leaf plot

http://mainland.cctt.org/mathsummer/josephbond/stemandplots/stem-and-leaf_std.htm

A stem-and-leaf-plot displays data in an organized shape and distribution by splitting each data value into a "stem" and "leaf". This is strategic way to organize a set of data with many large values, and this technique group the numbers with the same stems. For example, this maps per capita GNP Western Africa. You can see in the key that 4 is the stem, and 80 is the leaf, and together that represents an income of $480. These kind of plots are used to help analysts look over large amount of numbers, by putting the largest digits on the stem and digits in the smallest place as the leaves.

49. Box plot

http://rtutorialseries.blogspot.com/2010/02/r-tutorial-series-regression-with.html

A box plot graphically depict groups of numerical data in quartiles. It is a standard way to display the distribution of data using a summary of the minimum, first quartile, median, third quartile and maximum. For a map like this, you can see what a box plot is useful in giving us a visualization of statistical measures of a team's salary. You can easily discover all five of the variables mentioned, such as, who makes the most in the AFC? Who makes the least? What is the average salary? Additionally, a box plot allows you to compare one group with another (AFC vs NFC)  based on their min, max, mean values.

48. Histogram

http://www.ct4me.net/Ohio_Graduation_Math_Test_Prep_DataStrand.htm

A histogram is a graphical representation of data distribution. This graph display data of different heights, with the horizontal axis continuous in a progressive number line, while the other axis show how many students are in that range of height. Histogram is useful source to show distribution of data in categories such as weight, height, how much time, etc.

47. Parallel coordinate graph

http://vis.lbl.gov/Vignettes/Drosophila/index.html

A parallel coordinate graph display the relationship between multiple variables by visualizing high-dimensional geometry. Viewers can look at many different variables simultaneously. This example is interested in visualizing the expression of genes. By using a parallel coordinate graph, scientists are able to utilize spatial information and its relationship between different gene's expression patterns. The parallel coordinates represent each gene in a parallel axis where expression levels are defined on a point of each axis. Connecting these points of axes allow cell to be represented by a polyline.