Data‐Representation Passages on the ACT Science Test

By Lisa Zimmer Hatch, Scott A. Hatch

The ACT Science Test has two to three data‐representation passages, each with just five or six questions. When you encounter a data‐representation passage, you can use the following approach to get through it quickly and painlessly:

  1. Ignore the passage at first and jump right to the first question.

    No use wasting precious time reading or reviewing the passage details. There’s plenty of time for careful examination of the passage as you answer the questions.

  2. Examine the question for clues to where in the passage you’ll find the answer.

    Sometimes the clues will be obvious: “According to the table, when is flow rate greater?” Other times, you’ll know which table or graph to check based on the specific data referenced in the question.

  3. Look at the table, diagram, or graph (or, rarely, paragraph) indicated by the question.

    Identify what the graphic is displaying (for example, drug dosages, reaction times, kinetic energy, or astronomical distances).

  4. Look at what the columns, rows, axes, and so on represent and determine how they’re related to one another.

    An independent variable, or controlled variable, is the factor that the experimenter can change to a specific value, such as the amount of water added. The dependent variable is the factor that isn’t under the experimenter’s direct control, such as the amount of energy released. In other words, the dependent variable is dependent on the independent variable.

    The most typical relationship between columns, rows, axes, and so on is one in which one column, row, axis, and so on presents values for the independent, or controlled, variable and another shows what happens to the dependent variable. This figure presents a classic relationship.

    Example of a graph you may see on the Science Test.

    Example of a graph you may see on the Science Test.

    Here, the amount of growth factor added is the independent variable, and the plant height is the dependent variable. The experimenter can’t directly manipulate plant height. He or she can add a certain amount of growth factor but then has no choice but to wait and see what happens to the plant height.

    The ability to distinguish the independent from the dependent variable is essential to understanding many data‐representation passages. You may even get a question directly asking about this distinction.

  5. Note the units of measurement.

    Don’t freak out if the units are unfamiliar to you. Data‐representation passages always present units of measurement (even the bizarre ones) very clearly. The axes on graphs are usually labeled, legends typically accompany diagrams, and graphs, column and row headings usually include the units.

  6. Look for trends in the data, noting any significant shifts.

    In the plant growth graph in the figure, note that for the range of values shown on the graph, plant height steadily increases with increases in growth factor.