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This deck focuses on Evaluating And Modeling Experiments, giving you a quick way to review the definitions, rules, and examples that matter most for ACT Science.
Study Evaluating And Modeling Experiments in ACT Science with focused flashcards that help you recognize the idea, recall the key rule, and apply it in practice-style prompts.
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What does a high standard deviation indicate about a data set?
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Data points are spread out over a wide range. Values are far from the average, showing variability.
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This deck focuses on Evaluating And Modeling Experiments, giving you a quick way to review the definitions, rules, and examples that matter most for ACT Science.
Work through these flashcards in short sessions. Try to answer each prompt before flipping the card, then revisit any cards you miss until the explanation feels automatic.
Answer: Data points are spread out over a wide range. Values are far from the average, showing variability.
Answer: An inactive substance or treatment given to the control group. Controls for psychological effects of treatment expectation.
Answer: Random error. Unpredictable variations that cannot be controlled.
Answer: It approximates the overall trend relating the two variables. Shows the general relationship despite individual data scatter.
Answer: Double-blind study. Prevents bias from both subjects and researchers.
Answer: m=2. Slope = runrise=4−18−2=2
Answer: The group that receives the treatment or condition being tested. Allows comparison with control to measure treatment effects.
Answer: Introduce control variables to maintain constant conditions. Control variables prevent confounding of results.
Answer: Type of fertilizer. This is what the researcher changes or manipulates.
Answer: Plant height. The outcome variable affected by fertilizer treatment.
Answer: Light level. This uncontrolled factor could affect plant growth results.
Answer: Identify and control confounding variables. Eliminates alternative explanations for observed effects.
Answer: Correlation is association; causation requires a direct effect. Causation means one variable directly influences another.
Answer: Dependent variable. This responds to changes in the independent variable.
Answer: To evaluate and validate research findings. Experts check research quality before publication.
Answer: An external variable affecting both independent and dependent variables. Third variable that influences both measured variables.
Answer:
Answer: Soil type, water, and temperature. Controls for variables other than light intensity.
Answer: Sugar concentration. The factor deliberately varied to test effects.
Answer: An extraneous variable that affects the outcome of an experiment. Creates alternative explanations that invalidate results.
Answer: As x increases, y decreases. Variables move in opposite directions from each other.
Answer: Reaction rate. This variable responds to changes in temperature.
Answer: A factor that does not change throughout the experiment. Remains unchanged to isolate variable effects.
Answer: Time of day. The factor researchers control and manipulate.
Answer: The measured response that depends on the independent variable. This is what you measure to see the effect of changes.
Answer: A testable prediction about how the independent variable affects the dependent variable. States the expected relationship between variables.
Answer: b, the value of y when x=0. Shows where the line crosses the vertical axis.
Answer: To evaluate and validate research findings. Experts check research quality before publication.
Answer: To test feasibility and refine methodology. Small trial run identifies problems before main study.
Answer: The variable that is measured or observed in response to changes. It's the effect that researchers measure for changes.
Answer: Systematic error. Consistent bias in one direction affects all measurements.
Answer: An experimental design where the same subjects are used in all conditions. Reduces individual differences as confounding variables.
Answer: Use randomization to assign subjects to groups. Ensures equal chance of assignment to any group.
Answer: Results unlikely due to chance, suggesting a real effect. Low probability the results occurred by random chance.
Answer: To survey existing research and identify gaps. Examines previous studies to build research foundation.
Answer: b, the value of y when x=0. Shows where the line crosses the vertical axis.
Answer: Bar graph. Best for discrete categories or groups.
Answer: Repeating trials or experiments to check consistency of results. Confirms results are reliable and not due to chance.
Answer: y=9. Substitute x=4: y=2(4)+1=9
Answer: The dependent variable. Shows what researchers measure as the outcome.
Answer: The exact procedure used to measure or define the variable. Makes the measurement method clear and repeatable.
Answer: To simulate and analyze real-world processes to make predictions. Creates testable representations of complex systems.
Answer: Systematic error. Consistent bias in one direction affects all measurements.
Answer: Crop yield. The outcome measured in agricultural experiments.
Answer: Randomization. Eliminates bias by randomly assigning subjects.
Answer: b=5. Substitute point into y=mx+b: 11=3(2)+b, so b=5.
Answer: Extrapolation. Estimating beyond the observed data range is extrapolation.
Answer: Light level. This uncontrolled factor could affect plant growth results.
Answer: x=4. Substitute y=1: 1=5−x, so x=4
Answer: The variables change at an approximately constant rate. Data points form a straight line pattern.
Answer: The variable that is manipulated or changed by the experimenter. It's the cause that researchers control to test effects.
Answer: Group receiving placebo. This group receives no treatment for comparison.
Answer: An uncontrolled factor that can affect the dependent variable. Can create misleading results by affecting the outcome.
Answer: Systematic shifts results consistently; random varies unpredictably. Systematic error is predictable; random error is not.
Answer: It can be repeated with similar results. Other researchers get consistent results using same methods.
Answer: Reaction rate. This variable responds to changes in temperature.
Answer: Randomized experiment. Random assignment allows causal conclusions to be drawn.
Answer: It approximates the overall trend relating the two variables. Shows the general relationship despite individual data scatter.
Answer: Increase the sample size for more reliable results. Larger samples reduce random error and increase validity.
Answer: A data point far from the overall pattern or trend. May indicate measurement error or unusual conditions.
Answer: No linear relationship between variables. Variables are completely independent of each other.
Answer: Conduct multiple trials to ensure reliability. Single trials cannot establish reliable patterns.
Answer: No correlation (approximately constant y). Horizontal pattern shows y doesn't change with x.
Answer: Time of day. The factor researchers control and manipulate.
Answer: Specify measurable variables like growth rate and light condition. Hypothesis lacks measurable, operational definitions.
Answer: Negative correlation. Downward trend indicates negative relationship between variables.
Answer: Water temperature. The factor being deliberately manipulated by researchers.
Answer: Independent variable. The researcher controls and changes this factor.
Answer: Sampling bias. Sample doesn't accurately reflect the target population.
Answer: Neither participants nor researchers know assigned groups. Prevents bias from expectations affecting results.
Answer: Differences in results can be attributed to the independent variable. Only the treatment varies, so it caused any differences.
Answer: Controlled variable. These factors must remain constant to ensure valid results.
Answer: The results can be consistently replicated under the same conditions. Demonstrates reliability and validity of findings.
Answer: Differences in results can be attributed to the independent variable. Only the treatment varies, so it caused any differences.
Answer: To provide a basis for experimental testing. Creates testable predictions for experiments to verify.
Answer: Probability of observing results as extreme as the observed. Lower p-values suggest results are not due to chance.
Answer: Control group. Controls for psychological treatment effects.
Answer: Identify and control confounding variables. Eliminates alternative explanations for observed effects.
Answer: The no-fertilizer group. This group receives no treatment for comparison.
Answer: To propose a testable explanation or prediction. It guides the experiment and can be tested.
Answer: To interpret and draw conclusions from data. Extract meaningful patterns and relationships from results.
Answer: Experimentation. Controlled tests determine if hypotheses are supported.
Answer: Probability of observing results as extreme as the observed. Lower p-values suggest results are not due to chance.
Answer: Increase the sample size for more reliable results. Larger samples reduce random error and increase validity.
Answer: It can be repeated with similar results. Other researchers get consistent results using same methods.
Answer: Use randomization to assign subjects to groups. Eliminates selection bias in experimental design.
Answer: Develop a testable hypothesis to guide the experiment. Hypotheses provide direction and focus for research.
Answer: Use randomization to assign subjects to groups. Eliminates selection bias in experimental design.
Answer: m, the change in y per unit change in x. Shows how steep the line is and direction of change.
Answer: Temperature. The experimenter controls this variable to test its effect.
Answer: To prevent bias by keeping both subjects and experimenters unaware of group assignments. Eliminates expectation bias from all participants.
Answer: The variables change at an approximately constant rate. Data points form a straight line pattern.
Answer: An extraneous variable that affects the outcome of an experiment. Creates alternative explanations that invalidate results.
Answer: A group that does not receive the experimental treatment. Provides baseline comparison to show treatment effects.
Answer: The number of observations or subjects in an experiment. Larger sizes increase reliability and statistical power.
Answer: Estimating within the range of observed data. Predictions are more reliable within the data range.
Answer: Soil type, water, and temperature. Controls for variables other than light intensity.
Answer: The observed effect is unlikely due to random chance alone. The probability of getting this result by chance is very low.
Answer: A factor that does not change throughout the experiment. Remains unchanged to isolate variable effects.
Answer: The number of observations or subjects in an experiment. Larger sizes increase reliability and statistical power.