ACT Science key terms

A proposed, testable explanation for an observation that predicts what should happen under specified conditions. In ACT Science passages, hypotheses are usually stated as competing claims by different students or researchers.

A statement of what will be observed if a hypothesis is correct, often phrased as an if-then relationship. Predictions connect a proposed explanation to measurable outcomes.

The factor that a researcher deliberately changes or selects across trials. It is plotted on the horizontal axis of a graph and is used to organize comparisons between conditions.

The measured outcome that may change in response to the independent variable. It is plotted on the vertical axis and is the quantity used to judge whether a hypothesis is supported.

Any factor held constant across all trials so it cannot explain differences in results. Keeping these constant lets a study attribute observed changes to the independent variable.

Any quantity or condition that can take on different values in an investigation. Identifying which factors vary and which are fixed is a first step in interpreting any experiment.

A comparison group that does not receive the treatment being tested, or receives a neutral version of it. Its results show what would happen without the factor of interest.

The group that receives the treatment or condition under investigation. Comparing its results with the control group isolates the effect of the treatment.

The overall plan for a study, including what is varied, what is held constant, how many trials are run, and how measurements are taken. Sound design makes results interpretable.

The number of subjects or trials included in a study or in a single condition. Larger samples generally make results more reliable and reduce the influence of chance variation.

A single run or repetition of an experimental procedure under a specified set of conditions. Multiple trials help reveal whether a result is consistent or a one-time fluke.

The degree to which repeated measurements or repeated trials give consistent results. Reliable results are repeatable, though they are not automatically valid.

The degree to which a study actually measures or tests what it claims to. A study can be reliable yet invalid if it systematically measures the wrong thing.

A systematic error that pushes results in a particular direction rather than scattering them randomly. Sources include nonrepresentative samples, flawed measurement tools, or expectations influencing observations.

The difference between a recorded value and the true value, arising from instrument limits, reading technique, or natural fluctuation. It affects how precisely a result can be trusted.

How close repeated measurements are to one another, or how fine the scale of a measuring tool is. Precise measurements cluster tightly but may still be far from the true value.

How close a measured value is to the true or accepted value. Accurate results hit the target, while precise results merely agree with each other.

The range within which a true value is expected to lie, given the limits of measurement. It is often expressed as a plus-or-minus amount or as error bars on a graph.

The overall direction or pattern shown by data, such as increasing, decreasing, leveling off, or cycling. Describing a trend requires stating both direction and how the rate changes.

A relationship in which two variables tend to change together, either in the same direction or in opposite directions. Correlation alone does not establish that one variable causes the other.

A relationship in which a change in one variable directly produces a change in another. Establishing causation typically requires controlled experiments that rule out alternative explanations.

Estimating a value that falls between two known data points, using the pattern those points establish. It is generally more trustworthy than extrapolation because it stays inside observed data.

Estimating a value beyond the range of the collected data by extending an observed trend. It is riskier than interpolation because the trend may change outside the measured range.

The steepness of a line on a graph, equal to the change in the vertical quantity divided by the change in the horizontal quantity. Slope often represents a rate.

How much one quantity changes per unit change in another, such as grams per minute or meters per second. On a graph it appears as steepness, and it may itself change along a curve.

A relationship whose graph is a straight line, meaning the dependent variable changes by a constant amount for each unit change in the independent variable.

A relationship in which both variables increase together or both decrease together. On a graph, the line or curve generally rises from left to right.

A relationship in which one variable increases while the other decreases. On a graph, the line or curve generally falls from left to right.

The horizontal or vertical reference line of a graph, each labeled with a quantity and its units. Reading axis labels and scales correctly is essential before interpreting any plotted value.

The numerical spacing used along a graph axis or in a data table, such as increments of 1, 5, or 100. Misreading the scale is a common cause of wrong answers.

The standard of measurement attached to a number, such as seconds, grams, or degrees Celsius. Answers must be expressed in the units the question or graph specifies.

An organized grid of values in which rows and columns correspond to conditions and measured quantities. Column headings and units tell you what each number represents.

A line segment drawn through a plotted point showing the uncertainty or variability of that measurement. Overlapping error bars suggest the values may not truly differ.

A data point that lies far from the overall pattern of the other values. Outliers may reflect measurement error or a real but unusual condition and should be examined, not automatically discarded.

A judgment about what the results mean, ideally limited to what the data support. Strong conclusions state the direction of the effect and acknowledge the conditions under which it was found.

A simplified representation of a system used to explain observations and make predictions. Models are judged by how well their predictions match data, not by whether they are perfectly realistic.

A concise statement, often mathematical, describing a consistent pattern observed in nature, such as a relationship between force and acceleration. Laws describe regularities rather than explaining underlying mechanisms.

A broad, well-tested explanation for a body of observations that is supported by extensive evidence. In science, a theory is not a guess but a robust explanatory framework.