Hypotheses, Variables & Controls: Sixth Grade Science
Understanding variables and establishing experimental controls are the absolute cornerstones of valid scientific experimentation.
Deconstructing Experimental Variables
In any scientific investigation, variables are the conditions, quantities, or factors that can change, be manipulated, or be measured. To determine whether one event causes another, an investigator must carefully define and isolate three categories of variables: the independent variable, the dependent variable, and controlled variables.
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| THE THREE TYPES OF VARIABLES |
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| Variable Type | Definition & Function in Experiment |
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| Independent | The single factor deliberately manipulated or changed |
| Variable (IV) | by the investigator (The Cause). |
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| Dependent | The factor that responds to changes in the IV; the |
| Variable (DV) | measured outcome or collected data (The Effect). |
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| Controlled | All environmental factors kept identical across every |
| Variables (CVs) | experimental group to ensure a fair test. |
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The Independent Variable (The Cause)
The independent variable (also known as the manipulated variable) is the factor that the investigator intentionally alters to test its effects. A well-designed experiment tests only one independent variable at a time. If an investigator were to change both soil temperature and watering frequency simultaneously in a plant study, it would be impossible to determine which factor caused any observed difference in growth rate.
The Dependent Variable (The Effect)
The dependent variable (also known as the responding variable) is the factor that is measured or observed to evaluate the effect of the independent variable. Its value "depends" upon the independent variable. The dependent variable provides the quantitative or qualitative data recorded in tables and plotted on the vertical y-axis of a graph.
Controlled Variables (Constants)
Controlled variables—frequently referred to simply as constants—are all of the other variables in the experimental environment that must be maintained identically across all test groups. For example, if an experiment tests how light intensity affects photosynthesis, the controlled variables must include water volume, water temperature, ambient carbon dioxide concentration, species of plant, size of plant, and container size. Any uncontrolled variable introduces experimental error and compromises the validity of the investigation.
Experimental Groups Versus Control Groups
A controlled experiment divides test subjects into two essential groups: the experimental group and the control group.
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| EXPERIMENTAL VS. CONTROL GROUPS |
| |
| [ All Test Subjects Selected ] |
| | |
| +------------------+------------------+ |
| | | |
| v v |
| [ Control Group ] [ Experimental Group ] |
| | | |
| Standard Baseline Conditions Receives Independent Variable |
| (No Treatment Applied) (Specific Treatment Applied) |
| | | |
| +------------------+------------------+ |
| | |
| v |
| [ Compare Results & Calculate Difference ] |
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The Experimental Group
The experimental group consists of the test subjects, samples, or trials that are exposed to the independent variable. An experiment can have multiple experimental groups to test different levels or concentrations of the independent variable. For example, if testing the effect of motor oil viscosity on engine friction, the experimental groups might use 5W-20, 10W-30, and 20W-50 oil grades.
The Control Group
The control group serves as the standard baseline for comparison. It is treated with the exact same procedures and kept under the exact same conditions as the experimental group, with one single exception: it does not receive the independent variable treatment. Without a control group, an investigator cannot prove whether an observed change was caused by the independent variable or by natural baseline fluctuations in the environment.
Positive and Negative Controls
In advanced experimental design, scientists distinguish between two types of controls:
- A negative control group is a group where no response is expected. It confirms that the experimental procedure does not produce a false positive result on its own. For example, testing pure distilled water with a chemical indicator demonstrates what an empty, negative test looks like.
- A positive control group is exposed to a treatment known to produce the expected effect. It verifies that the experimental setup, measuring tools, and reagents are functioning correctly.
Formulating a Strong, Testable Hypothesis
A rigorous hypothesis is not an uneducated guess; it is a reasoned prediction grounded in scientific theory and factual observations. It must explicitly state the relationship between the independent variable and the dependent variable, and it must include a logical rationale.
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| ANATOMY OF A SCIENTIFIC HYPOTHESIS |
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| "IF [manipulation of independent variable], |
| THEN [predicted response of dependent variable], |
| BECAUSE [scientific principle or established mechanism explaining why]." |
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Exercises and Solutions
Exercise 1: Identifying Variables in an Aerodynamics Experiment. A student wants to determine how wing surface area affects the glide distance of an unpowered glider. The student constructs four identical balsa-wood gliders with wing areas of 100 square centimeters, 150 square centimeters, 200 square centimeters, and 250 square centimeters. Each glider has the same total fuselage mass of 45 grams, is launched using a mechanical spring-loaded launcher with 10 newtons of tension, and is released indoors in an air-conditioned gymnasium with no wind. Identify: (a) the independent variable; (b) the dependent variable; (c) three controlled variables; and (d) explain what would happen to the validity of the experiment if the student threw each glider by hand instead of using the mechanical launcher.
Solution 1: (a) The independent variable is the wing surface area of the gliders (100, 150, 200, and 250 square centimeters). (b) The dependent variable is the glide distance traveled by each glider (measured in meters). (c) Three controlled variables are the total mass of the gliders (45 grams), the launch force (10 newtons), and the indoor environment (no crosswinds or drafts). (d) If the student launched each glider by hand, the launch force, release angle, and launch speed would vary randomly on every throw. This would introduce uncontrolled confounding variables, making it impossible to determine whether differences in flight distance were caused by wing area or by human throwing inconsistencies.
Exercise 2: Evaluating the Necessity of a Control Group. An agricultural researcher tests a new organic microbial spray designed to protect apple trees from fungal leaf spots. The researcher sprays fifty apple trees in an orchard with the microbial mixture and observes that after two months, only two trees show signs of fungal infection. The researcher concludes that the microbial spray is 96 percent effective at preventing fungal leaf spots. Explain why this conclusion is scientifically invalid without a control group, and describe how the researcher should have structured the experiment.
Solution 2: The conclusion is invalid because without an untreated control group, the researcher cannot determine whether the low infection rate was caused by the microbial spray or by external environmental factors such as dry weather, strong sunlight, or the absence of fungal spores in the orchard. To structure a scientifically valid experiment, the researcher should have selected one hundred identical apple trees growing in the same soil and climate conditions. Fifty trees (the experimental group) would receive the microbial spray, while the remaining fifty trees (the control group) would be sprayed with plain water. Comparing the infection rates between both groups under identical conditions would prove whether the spray provided measurable protection.