Being the clever inquisitor you are, you probably are wondering next: what if the data set is huge, and there are tons of variables? How the heck am I going to be able to sift through all of that information to determine anything?? Well, the answer is this: graphs. Remember how you made bar graphs and pie graphs in elementary school? It's the same thing!!
Graphs allow the viewer to quickly see what's going on in the data set, as opposed to just looking at a bunch of numbers. It gives a great visual interpretation of the distribution which in turn allows quick analysis of the overall pattern, the deviations, shape, spread, the center, symmetry, and outliers. These will be discussed more in depth in the next section. Other graphs that are used are histograms, which is the distribution of one quantitative variable. This graph is very common and is useful because nearby values are grouped together.
At different times it is useful to use different graphs. Stemplots for small data sets, dotplots for a quick visual interpretation, and histograms which group common values together. Indeed, when analyzing data sets, choose your weapon wisely.
