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After running experiments and making observations, a scientist is left with a large collection of information, or data, to use to draw a conclusion. Trying to find patterns in page after page of descriptive observations or lists of numbers is almost impossible. To find patterns in the data, a scientist uses statistics.

Statistics are a mathematical tool for describing and comparing information (observations) quantitatively, which simply means using numbers. By using numbers to describe the data, such as the number of times a certain characteristic is observed in different rock samples, scientists can organize and compare the patterns in the data using simple arithmetic.

Some people find statistics intimidating because they seem like complicated mathematical formulas. But really, statistical methods are simple mathematics combined in a step-by-step sequence to uncover patterns in the data. Some statistics determine if two sets of data have overall similarities or differences. Others determine which variables are most important in creating the observed outcomes.

Another reason scientists organize and describe their data quantitatively is so that they can display it using graphs. Many different types of graphs are used, and a scientist must determine which type of graph best displays the data in an understandable way. The most suitable graph depends on what type of data is being displayed. Figure 2-1 illustrates a few common graph types used in earth science:

 Pie graph: This type of graph is best used for illustrating different pieces of a whole. The total of a pie chart must always add up to 100 percent.

 Bar graph: Also called histograms, bar charts are used to display information that can be sorted into different categories.

 Scatterplot: Scatterplot graphs illustrate how two types of data are related. Sometimes a scientist will use a scatterplot to look for patterns of relationship between the data types — by finding clusters of data points.

 Line graph: This type of graph is most commonly used to plot changes in a type of data over time, distance, or other variable.

FIGURE 2-1: a) Pie graph; b) Bar graph; c) Line graph; d) Scatterplot.