GED Science Practice Test: Representing Scientific Data: Tables and Graphs
When a scientist attempts to make sense of the data collected in an experiment, he or she will often choose to represent the data visually through tables and graphs. A data table is a common method for initially collecting the data, though a graph can often make patterns in the data easier to discern. The first step to using graphs to make patterns apparent is selecting the right kind of graph for the collected data. Below are some of the common types of graphs and their purpose.
Bar Graph: A bar graph is used to represent values (numbers) that are organized by category. For example, a bar graph might be used to show the number of pets owned by a class of students:
Bar graphs can have vertical bars (like the graph above) or it can have horizontal bars. Regardless, on one axis, you will have a category (like type of pet), and on the other axis, you will have a number (like number of people).
In terms of variables in an experiment, the categories usually represent the independent variable and the numbers represent the dependent variable. So if you are conducting an experiment that has the independent variable divided up into categories, you will likely use a bar graph.
Scatter Plots: A scatter plot is used to compare two sets of numbers. For example, a scatter plot might be used to show how the number of visitors to the beach changes with increasing daily temperature:
In terms of variables, if both the independent and dependent variables involve numbers, you will likely use a scatter plot. In the above example, both average daily temperature and visitors involve numbers. Additionally, the independent variable is normally placed on the x-axis (the horizontal one), and the dependent variable is placed on the y-axis (the vertical one). In the above example, it may be odd to think of the average daily temperature as manipulated (i.e., the scientist did not change the daily temperature). But it is the thing upon which the number of visitors depends.
Sometimes, a trend line (or line of best fit) will be placed on a scatter plot to better show the pattern. A trend line roughly cuts the data points in half, with approximately half of the data points being above the line, and half of the data points being below the line. Such a trend line or line of best fit helps a scientist to describe the numerical relationship between the variables. Below is an example of a trend line:
Line Graphs: Line graphs are different from scatter plots with trend lines. In line graphs, the data points are actually connected together. You often see line graphs used to show the change in a variable over time. In an experiment involving time, the dependent variable changes from one value to the next, and thus, it makes sense to connect those values together. The following is an example of a line graph:
In terms of variables, if the independent variable is time, and the dependent variable is a number, you will use a line graph. Time is the independent variable, and is placed on the x-axis. The number is the dependent variable, and is placed on the y-axis.
Pie Chart: Pie charts show percentages or portions of a whole. A large circle is divided into sections depending on those percentages and each section represents part of the whole. The following is an example of a pie chart:
In terms of variables, the independent variable should be a category, and is shown in the key. The size of the “slices” of the pie show the dependent variable for each category. The dependent variable should be a percentage (or should be converted to a percentage).
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