ACT Science Quiz: Evaluating And Modeling Experiments

What this quiz covers

This quiz focuses on Evaluating And Modeling Experiments, giving you a quick way to practice the rules, question types, and explanations that matter most for ACT Science.

How to use this quiz

Try each quiz question before looking at the correct answer. Use the explanations to review missed ideas, then come back to similar questions until the pattern feels familiar.

Question 1

1. The temperature during the experiment (correct answer)
2. The type of plant used in the experiment
3. The duration of exposure to humidity
4. The initial weight of each plant

Explanation: The independent variable is humidity level, the dependent variable is plant transpiration (measured by weight loss), and variables like plant size, soil moisture, and light exposure should be controlled. The critical confounding factor is temperature during the experiment, which significantly affects both transpiration rate and humidity levels, making it impossible to isolate humidity's independent effect. Choice A correctly identifies this confounding variable, as temperature changes would alter transpiration rates regardless of humidity manipulation, creating a situation where two variables change simultaneously. Choice D describes a controlled parameter rather than a confounding variable.

Question 2

1. No control group without sunlight was included.
2. The duration of the experiment was too short.
3. Temperature was not controlled between groups. (correct answer)
4. The height measurement method was not specified.

Explanation: The independent variable is sunlight exposure (direct vs. shaded), the dependent variable is plant height, and variables like temperature, water, soil type, and humidity should be controlled. The critical flaw is that temperature was not controlled between the sunlight and shaded groups, creating a confounding variable that could affect plant growth independently of sunlight. Choice C correctly identifies this major experimental design issue, as temperature differences between sunny and shaded locations could influence growth rates regardless of light exposure. Choice A is incorrect because having both sunlight and shade groups already provides the necessary comparison - a completely dark control isn't required to test the effect of sunlight versus shade.

Question 3

1. Using a different type of plant species
2. Including a group with no fertilizer (correct answer)
3. Changing the soil type for each plant
4. Altering the amount of sunlight each plant receives

Explanation: The independent variable is fertilizer amount, the dependent variable is plant growth, and variables like sunlight, water, and soil type should be controlled. To properly test the effect of fertilizer, the experiment needs a baseline comparison group that receives no fertilizer treatment at all. Choice B correctly identifies this missing control group, which would establish whether fertilizer has any effect compared to natural growth conditions. Choice C would actually worsen the experiment by introducing soil type as a confounding variable, making it impossible to isolate the effect of fertilizer alone.

Question 4

1. Repeat each salt condition in multiple trials and average the freezing temperatures to reduce random variation. (correct answer)
2. Use larger beakers so the water cools more slowly and ice crystals are easier to see.
3. Remove the 0 g salt beaker, because controls are unnecessary when comparing two salt concentrations.
4. Open the freezer door more frequently, because more checks increase the accuracy of the first-crystal observation.

Explanation: The independent variable is salt mass (0g, 5g, 10g), the dependent variable is freezing temperature, and variables like water volume and freezer conditions were controlled. The major limitation is that each condition was tested only once, making the results unreliable due to random measurement error and variation. Choice A correctly suggests repeating trials and averaging results to reduce the impact of random variation and increase confidence in the observed differences. This is especially important when measuring precise temperatures where small variations could affect conclusions. Choice B about larger beakers doesn't address reliability, Choice C incorrectly eliminates the necessary control group, and Choice D would actually decrease accuracy by introducing more temperature fluctuations from frequent door opening.

Question 5

1. The type of plant used.
2. The color of light used is not varied.
3. The temperature of the environment.
4. The intensity of light is not constant. (correct answer)

Explanation: The independent variable is light color, the dependent variable is photosynthesis rate, and controlled variables should include light intensity, temperature, and plant type. Choice D correctly identifies that inconsistent light intensity introduces a confounding variable, since both color and intensity affect photosynthesis rates. If different colored lights have different intensities, any observed effects cannot be attributed solely to color, making it impossible to isolate the independent variable's impact. Light intensity must be kept constant across all color treatments to ensure valid results. The other factors listed are either controlled variables that should remain constant or design elements that don't introduce confounding effects.

Question 6

1. The experiment lacks a water control.
2. The liquid type is not varied enough.
3. Corrosion rate is not a suitable measure.
4. The type of metal is not specified. (correct answer)

Explanation: The independent variable is liquid type, the dependent variable is corrosion rate, and controlled variables should include temperature, exposure time, and metal surface preparation. Choice D correctly identifies that the type of metal is not specified as a critical flaw, since different metals have vastly different corrosion susceptibilities and mechanisms. Without standardizing the metal type, any observed differences cannot be attributed solely to the liquid effects, as metal composition would confound the results. The same metal type should be used across all liquid treatments to isolate the liquid's impact. Choice A suggests adding a water control, which would be helpful but doesn't address the fundamental design flaw of uncontrolled metal type.

Question 7

1. Define drying time using an objective test, such as mass loss stabilization or a standardized tack test, not finger feel. (correct answer)
2. Use different brands of paint for each color, because brands represent real-world variation in paint chemistry.
3. Paint the boards at different times of day, because varying sunlight ensures the fastest color will still dry fastest.
4. Remove the black board, because extreme results can distort conclusions about typical paint drying behavior.

Explanation: The independent variable is paint color (white, red, blue, black), the dependent variable is drying time, and variables like brand, boards, and conditions were controlled. The major validity issue is the subjective measurement of 'drying' based on the student's finger feel, which introduces measurement bias and inconsistency. Choice A correctly suggests using objective measures like mass loss stabilization or standardized tack tests that would provide consistent, reliable drying endpoints. This eliminates subjective judgment and improves measurement validity. Choice B introduces unnecessary brand variation that would confound color effects, Choice C adds time-of-day variation that could affect drying, and Choice D inappropriately excludes the black sample that shows an interesting heat absorption effect.

Question 8

1. Phone model, because using identical phones prevents observing how cases work across different devices.
2. Battery starting charge, because both phones began at 100% and therefore were not comparable.
3. Game duration, because 20 minutes is too short to produce any measurable temperature difference.
4. Network connection type, because Wi-Fi versus cellular data can change power use and heat generation during gaming. (correct answer)

Explanation: The independent variable is phone case presence (with vs without case), the dependent variable is maximum battery temperature, and variables like phone model, game, and starting charge were controlled. The uncontrolled variable is network connection type, where Phone 1 used Wi-Fi while Phone 2 used cellular data. This creates a confounding variable because cellular data transmission typically requires more power and generates more heat than Wi-Fi, which could explain the temperature difference independent of the case effect. Choice D correctly identifies this confounding factor that undermines the conclusion about case effectiveness. Choice B incorrectly suggests identical starting charges prevent comparison, when actually they ensure fair comparison, and Choice A misunderstands that identical phones are needed to isolate the case variable.

Question 9

1. The student should have used a longer typing passage, because short passages cannot measure typing speed accurately.
2. Keeping the same laptop model for all participants prevents generalizing results to other computers, invalidating the conclusion.
3. Allowing participants to choose drink type introduces self-selection bias, so groups may differ in baseline typing ability. (correct answer)
4. Measuring WCPM instead of total words typed confounds speed with accuracy, so caffeine effects cannot be detected.

Explanation: The independent variable is drink type (caffeinated vs decaffeinated tea), the dependent variable is typing speed (WCPM), and variables like room conditions and passage were controlled. The major flaw is that participants self-selected their drink preference rather than being randomly assigned to conditions. This introduces selection bias because people who choose caffeine may already be different in baseline typing ability, alertness, or motivation compared to those who avoid caffeine. Choice C correctly identifies this confounding factor that could explain the observed differences without any true caffeine effect. Choice A incorrectly focuses on passage length, which wouldn't systematically bias results between groups, while Choice D misunderstands that WCPM appropriately measures both speed and accuracy together.

Question 10

1. Remove the water condition, because dehydration effects can be inferred without comparing to a hydrated group.
2. Randomly assign participants to hydration conditions, because self-selection may correlate with fitness or usual hydration habits. (correct answer)
3. Measure heart rate only after 30 minutes, because immediate measurements are always less accurate than delayed ones.
4. Allow participants to run different distances, because varying exercise intensity makes hydration effects easier to observe.

Explanation: The independent variable is hydration condition (water vs no water), the dependent variable is heart rate after exercise, and variables like exercise duration and measurement timing were controlled. The validity issue is that participants self-selected their hydration condition rather than being randomly assigned, potentially creating selection bias. People who choose to hydrate may differ systematically in fitness level, usual hydration habits, or health consciousness compared to those who choose not to drink water. Choice B correctly identifies this selection bias that could confound hydration effects with pre-existing participant differences. Random assignment would eliminate this bias and ensure groups are comparable. Choice D incorrectly adds exercise intensity variation that would confound the hydration variable.

Question 11

1. The same teacher was used for all methods.
2. Student prior knowledge was not controlled. (correct answer)
3. The duration of each teaching method varied.
4. The study did not account for student preferences.

Explanation: The independent variable is teaching method (lectures, discussions, projects), the dependent variable is student performance, and variables like student ability, content difficulty, and instructor skill should be controlled. The critical flaw is that students' prior knowledge was not controlled or assessed before the study, creating a confounding variable that could affect performance independent of teaching method. Choice B correctly identifies this major design issue, as students with different background knowledge levels might perform differently regardless of the teaching method used, making it impossible to isolate the method's true effectiveness. Choice A describes a controlled aspect rather than a confounding variable.

Question 12

1. The experiment lacks a no-salt control group. (correct answer)
2. The boiling point is an unsuitable dependent variable.
3. The experiment should use different types of salt.
4. Salt concentration is not varied enough.

Explanation: The independent variable is salt concentration, the dependent variable is boiling point, and controlled variables should include atmospheric pressure and heating method. Choice A correctly identifies that the experiment lacks a no-salt control group, which is essential for establishing the baseline boiling point of pure water. Without this control, researchers cannot determine the magnitude of salt's effect on boiling point elevation. A proper control group allows comparison between treated (salt solutions) and untreated (pure water) conditions, making it possible to quantify the actual change caused by the independent variable. The other choices address experimental scope or variable selection but don't identify fundamental design flaws.

Question 13

1. Including white light is invalid, because white light is a mixture and cannot be compared to single colors.
2. Using 14 days is too long, because plants adapt and therefore color effects disappear after one week.
3. Not measuring actual light intensity across colors could confound color with brightness, so the independent variable is unclear. (correct answer)
4. Using plant mass is incorrect, because only height can indicate growth under different light colors.

Explanation: The independent variable is light color (red, blue, white), the dependent variable is plant mass, and variables like plant type, duration, and distance were controlled. The critical flaw is that equal electrical power doesn't guarantee equal light intensity (photon flux) across different colored LEDs, as different colors have different luminous efficacy. This means the plants may have received different amounts of usable light energy, confounding color effects with brightness effects. Choice C correctly identifies that the independent variable (light color) is unclear when intensity isn't controlled, since both color and brightness could affect growth. Choice D incorrectly dismisses plant mass as a growth measure, when mass reflects overall biomass accumulation better than height alone.

Question 14

1. The participants' physical activity levels (correct answer)
2. The duration of the diet trial
3. The specific foods included in each diet
4. The time of day energy levels were measured

Explanation: The independent variable is diet type (high protein vs. high carbohydrate), the dependent variable is energy levels, and variables like sleep, stress, and medical conditions should be controlled. The critical confounding factor is participants' physical activity levels, which can significantly affect energy levels independent of diet composition. Choice A correctly identifies this uncontrolled variable, as more active participants might report different energy levels regardless of their assigned diet, making it impossible to isolate the diet's true effect. Choice C describes a controlled aspect of the experimental design rather than an uncontrolled confounding variable.

Question 15

1. Use multiple test strips per sample and average results, because the strip's stated uncertainty is large relative to the change. (correct answer)
2. Switch to bottled water, because tap water contains too many variables to study filtration effects.
3. Filter the water twice, because stronger filtering always produces more accurate measurements of lead concentration.
4. Measure water temperature, because lead concentration depends primarily on temperature rather than filtration.

Explanation: The independent variable is filtration (before vs after filtering), the dependent variable is lead concentration, and the same water source was used. The reliability issue is that the observed change (0.08 to 0.04 ppm) is comparable to the test strip uncertainty (±0.03 ppm), making the result potentially within measurement error rather than indicating real filtration effect. Choice A correctly suggests using multiple strips per sample and averaging to reduce measurement variability and increase confidence in the observed difference. This follows the manufacturer's recommendation for reliable readings. Choice C incorrectly suggests additional filtering changes the experimental design, Choice B eliminates the realistic testing scenario, and Choice D misidentifies temperature as the primary factor affecting lead concentration.

Question 16

1. The baking temperature is not consistent. (correct answer)
2. The type of flour used is not varied.
3. The type of sugar is not varied.
4. The baking time varies for each batch.

Explanation: The independent variable is sugar type, the dependent variable is cookie texture score, and controlled variables should include baking temperature, time, flour type, and oven conditions. Choice A correctly identifies that inconsistent baking temperature introduces a confounding variable, since temperature dramatically affects cookie texture regardless of sugar type. If different batches are baked at different temperatures, any texture differences cannot be attributed solely to sugar type, making it impossible to isolate the independent variable's effect. Baking temperature must remain constant across all sugar treatments for valid comparisons. Choice D (varying baking time) would also be problematic, but temperature consistency is typically more critical for texture outcomes.

Question 17

1. Conduct the study in different environments
2. Include a group with no hydration (correct answer)
3. Measure performance over a longer period
4. Vary the types of hydration sources used

Explanation: The independent variable is hydration level, the dependent variable is cognitive performance, and variables like task difficulty, environment, and participant characteristics should be controlled. To properly test whether hydration affects cognitive performance, the experiment needs a control group with no hydration or baseline hydration levels for comparison. Choice B correctly identifies this missing control group, which would establish whether increased hydration produces different cognitive performance compared to normal or restricted hydration conditions. Without this control, it's impossible to determine if hydration has any effect versus other factors affecting cognitive performance.

Question 18

1. Adding a trial with no light (correct answer)
2. Using a different plant species
3. Changing the intensity of the light
4. Varying the duration of light exposure

Explanation: The independent variable is light wavelength (red, blue, green), the dependent variable is photosynthesis rate, and variables like light intensity, temperature, and plant condition should be controlled. To properly test the effect of different wavelengths, the experiment needs a control group with no light exposure to establish baseline photosynthesis levels. Choice A correctly identifies this missing control trial, which would determine if colored light produces different photosynthesis rates compared to darkness, establishing whether any wavelength effect exists at all. Choice C would introduce light intensity as a confounding variable, making it impossible to isolate wavelength effects.

Question 19

1. The type of exercise performed
2. The duration of the exercise sessions
3. The self-reported nature of mood surveys (correct answer)
4. The frequency of exercise sessions

Explanation: In this design the manipulated variable is which kind of exercise participants perform, aerobic or anaerobic, and the measured outcome is mood improvement. Because mood is captured only by a self-report survey, the outcome measure can be pushed around by things that have nothing to do with the exercise, including a participant's expectations about whether exercise should help and the pull toward giving socially acceptable answers. That uncontrolled influence on the results is the confounding element here. The type of exercise performed is the variable the study is deliberately comparing, not a confound. The 30-minute sessions and the daily schedule are both held the same for everyone, so duration and frequency are controlled features of the design rather than sources of hidden bias.

Question 20

1. Counterbalance or randomize alarm order across participants and use an independent observer or sensor to measure standing time. (correct answer)
2. Increase the alarm volume each night, because louder alarms reduce variability and ensure participants wake reliably.
3. Use only the new alarm for all nights, because repeated exposure to the standard alarm could reduce motivation.
4. Measure how much participants like each alarm, because preference is a more direct measure of waking effectiveness than time.

Explanation: The independent variable is alarm type (standard vs new), the dependent variable is standing time, and sleep location was controlled. Multiple validity issues exist: alarm order wasn't randomized (always standard first), participants knew which alarm was being tested (expectation bias), and participants self-measured response time (measurement bias). Choice A correctly suggests counterbalancing alarm order and using objective measurement to eliminate these biases. Randomizing order controls for night-to-night differences and practice effects, while independent measurement eliminates self-reporting bias and expectation effects. These changes would dramatically improve experimental validity. Choice C incorrectly eliminates the comparison condition needed to evaluate the new alarm's effectiveness.