ACT Science: Experimental Design and Hypotheses Quiz Quiz

This quiz explores core concepts of ACT Science, focusing on experimental design, variables, and hypothesis evaluation. Strengthen your scientific reasoning by analyzing testable questions, independent and dependent variables, and result interpretations within practical scenarios.

1. Identifying the Independent Variable

   In an experiment testing how different amounts of sunlight affect the growth rate of tomato plants, which element is acting as the independent variable?

   1. The amount of sunlight received
   2. The number of leaves produced
   3. The height of each plant
   4. The type of soil used

   Explanation: The independent variable is what the experimenter purposely changes, which in this experiment is the amount of sunlight. The height of each plant and number of leaves produced are measurements—likely dependent variables—affected by the sunlight. The type of soil, if kept constant, is a controlled variable, not the one being tested. Only the amount of sunlight received aligns with the definition of an independent variable.

2. Forming a Scientific Hypothesis

   A student predicts that using colder water will slow the rate at which salt dissolves. Which of the following represents the best hypothesis for this experiment?

   1. Cold salt dissolves better than warm salt.
   2. Hot water is best for dissolving salt.
   3. Salt changes water's temperature.
   4. If water is cold, salt will dissolve more slowly.

   Explanation: A proper hypothesis should be testable and declare a cause-and-effect relationship, such as 'If water is cold, salt will dissolve more slowly.' The choice about hot water makes an unsupported claim without a direct comparison. 'Salt changes water's temperature' is unrelated to dissolution rate, and 'Cold salt dissolves better than warm salt' does not match the original prediction involving water temperature.

3. Recognizing a Dependent Variable

   During a chemical reaction experiment, a student records the time it takes for a color change to occur after adding a catalyst. What is the dependent variable in this scenario?

   1. The time until color change
   2. The amount of catalyst used
   3. The initial water temperature
   4. The type of beaker

   Explanation: The dependent variable is what the experiment measures—in this case, the time until the color change. The amount of catalyst used and the initial water temperature are set by the experimenter and could be independent or controlled variables. The type of beaker is a procedural detail, not a measured outcome. Thus, timing the color change is the correct dependent variable.

4. Interpreting Controls in Experimental Design

   When testing if a fertilizer increases plant growth, which of the following is the best example of a control group?

   1. Plants that get extra water
   2. Plants that receive no fertilizer
   3. Plants grown with a different fertilizer
   4. Plants placed in sunlight longer

   Explanation: A control group does not receive the variable being tested, which is the fertilizer. This allows experimenters to compare results and see if fertilizer has an effect. Extra water or additional sunlight introduce new variables, which invalidates the control. Using a different fertilizer creates another treatment group rather than a true control.

5. Evaluating an Experimental Conclusion

   A scientist concludes that increasing temperature speeds up bacteria growth because cultures at 37°C grew faster than those at 20°C, with all other conditions unchanged. Which aspect makes this conclusion valid?

   1. The scientist measured growth with a ruler
   2. All cultures were left open to the air
   3. The experiment used many different bacteria species
   4. Only the temperature was changed between groups

   Explanation: Changing only one factor, the temperature, allows the scientist to attribute differences in growth to that variable. Using different bacteria species would introduce additional variables and confound results. Leaving cultures open to air risks contamination. Measuring with a ruler may not be suitable for bacteria, but does not address experimental validity. Isolating temperature as the sole change validates the conclusion.