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This deck focuses on Comparing Viewpoints And Hypotheses, giving you a quick way to review the definitions, rules, and examples that matter most for ACT Science.
Study Comparing Viewpoints And Hypotheses 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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Which option best defines a control condition in an experiment discussion?
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A baseline condition used for comparison to isolate the tested factor. Standard reference point to show the effect of experimental changes.
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This deck focuses on Comparing Viewpoints And Hypotheses, 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: A baseline condition used for comparison to isolate the tested factor. Standard reference point to show the effect of experimental changes.
Answer: Larger samples increase reliability and generalizability. More subjects reduce random error and improve statistical power.
Answer: Reliability. Consistent results indicate the measurement tool is dependable.
Answer: Questioning the validity of a claim without evidence. Requires evidence before accepting claims as scientifically valid.
Answer: Both subjects and researchers are unaware of group assignments. Eliminates bias from both participants and researchers.
Answer: Hypothesis. Requires testing through experimentation to become validated.
Answer: A range of values that likely contain the true parameter. Shows uncertainty around the estimated value.
Answer: The measured outcome that changes in response to the independent variable. What you measure as a result of changing other factors.
Answer: Evaluation by other experts in the field. Ensures quality and credibility of research.
Answer: Inference. Logical deduction based on available evidence and data.
Answer: The number of subjects or observations in a study. Determines how many participants are included.
Answer: Hypothesis A. Constant Y contradicts Hypothesis A's claim of dependence.
Answer: You can compare logic but cannot confirm which is correct. Without data, you can only assess internal consistency.
Answer: Each viewpoint may apply in a different range of conditions. Different conditions may favor different mechanisms or viewpoints.
Answer: Dependent variable. Changes in response to independent variable manipulation.
Answer: Reproducibility. Results can be repeated by different researchers.
Answer: To demonstrate that a hypothesis is incorrect. Falsification provides evidence against a proposed explanation.
Answer: Achieving consistent results in repeated trials. Independent researchers get the same results.
Answer: The factor deliberately changed or compared by the investigator. The variable you manipulate to test its effect.
Answer: Conducting an experiment. Controlled experiments provide data to support or refute predictions.
Answer: Choose the viewpoint whose mechanism predicts that observation. Match the observation to each viewpoint's logical predictions.
Answer: Option A: Y∝X. Direct proportionality means doubling input doubles output.
Answer: Scientific theory. Extensive testing builds strong scientific support.
Answer: Reproducibility. Results can be repeated by different researchers.
Answer: It predicts numerical relationships or specific measurable values. Makes specific numerical predictions that can be measured.
Answer: Null hypothesis. Assumes no change or difference will occur in the experiment.
Answer: It makes a prediction that could be checked with measurements. Testability requires specific, measurable predictions.
Answer: Null result. When data doesn't support the predicted outcome.
Answer: A range of values that likely contain the true parameter. Shows uncertainty around the estimated value.
Answer: It describes direction or type of change without numerical values. Describes trends or patterns without specific measurements.
Answer: A proposed explanation or prediction that can be tested. Must be specific enough to allow experimental testing.
Answer: They cannot both be true simultaneously. Only one can be correct when they contradict each other.
Answer: A hypothesis that assumes no effect or relationship. Default assumption that there's no difference or effect.
Answer: Confounding variable. Unwanted factor that influences experimental results.
Answer: A specific expected result under stated conditions. Must be concrete and verifiable through observation or experiment.
Answer: It predicts numerical relationships or specific measurable values. Makes specific numerical predictions that can be measured.
Answer: A testable statement predicting an outcome. Must be specific and measurable to enable testing.
Answer: To survey existing knowledge and identify gaps. Establishes foundation and context for new research.
Answer: The ability of a hypothesis to be proven false. Must be possible to disprove through testing.
Answer: The passage provides insufficient information to decide. Lack of relevant data makes evaluation impossible.
Answer: Analysis of variance. Compares multiple groups to identify differences.
Answer: Inductive reasoning. Moves from specific observations to broader generalizations.
Answer: Inference. Logical deduction based on available evidence and data.
Answer: Incorrectly rejecting the null hypothesis. False positive - claiming effect when none exists.
Answer: The data pattern matches the viewpoint's prediction. The data confirm what the viewpoint predicted would happen.
Answer: Dependent variable. This variable responds to changes in the independent variable.
Answer: Option B: Y∝X1. Inverse proportionality means doubling input halves output.
Answer: Null hypothesis. Assumes no change or difference will occur in the experiment.
Answer: A plan for conducting an experiment. Framework that guides data collection and analysis.
Answer: Each viewpoint may apply in a different range of conditions. Different conditions may favor different mechanisms or viewpoints.
Answer: As X increases, Y decreases. Negative correlation means variables move in opposite directions.
Answer: Qualitative is descriptive; quantitative is numerical. Qualitative uses words; quantitative uses numbers and measurements.
Answer: To provide a basis for experimentation. Guides experimental design and data collection methods.
Answer: To test the effect of the independent variable. Receives the treatment being studied to measure its impact.
Answer: To evaluate the validity of each viewpoint. Comparing helps identify which explanations are supported by evidence.
Answer: P-value. Lower values indicate less likely due to chance.
Answer: To provide a testable statement that guides research. Directs the experiment and enables focused testing.
Answer: Viewpoint A. Constant Y matches Viewpoint A's prediction exactly.
Answer: Blind study. Prevents bias from subject expectations.
Answer: The passage provides insufficient information to decide. Lack of relevant data makes evaluation impossible.
Answer: Deductive reasoning. Moves from general principles to specific conclusions.
Answer: Y is proportional to X2. The relationship follows a quadratic pattern with X.
Answer: The variable that is manipulated by the researcher. Researcher controls this to test its effects.
Answer: Null hypothesis. Scientists try to disprove it to support the alternative hypothesis.
Answer: Y is directly proportional to X. Linear relationship passing through origin indicates direct proportionality.
Answer: A scientist or student's stated explanation, claim, or model. Represents one scientist's interpretation or theoretical position.
Answer: Empirical data. Based on observation and experimentation.
Answer: Inference. Logical reasoning from observations to reach supported conclusions.
Answer: A variable, mechanism, or condition one includes and the other does not. A factor that separates one hypothesis from another.
Answer: Detailed documentation of methods. Others must be able to repeat the procedure.
Answer: Scientific inquiry. Methodical approach to discovering knowledge.
Answer: P-value. Lower values indicate less likely due to chance.
Answer: The described process explaining how the outcome occurs. The step-by-step process explaining the cause-effect relationship.
Answer: Confounding variable. Uncontrolled factors that might affect the dependent variable.
Answer: The action of causing an effect. One factor directly produces a change.
Answer: Detailed documentation of methods. Others must be able to repeat the procedure.
Answer: Validity. Measures how well results reflect the true phenomenon.
Answer: The data pattern contradicts the viewpoint's prediction. The data show the opposite of what was predicted.
Answer: As X increases, Y decreases. Negative correlation means variables move in opposite directions.
Answer: Dependent variable. Changes in response to independent variable manipulation.
Answer: A testable prediction or explanation for a phenomenon. Hypotheses must be specific and measurable to allow scientific testing.
Answer: Null hypothesis. Scientists try to disprove it to support the alternative hypothesis.
Answer: Both can be true because they do not logically conflict. No logical contradiction exists between the two claims.
Answer: Unlikely to have occurred by chance, indicating a real effect. Low probability the result occurred randomly.
Answer: A relationship between two variables. Shows association but not necessarily causation.
Answer: Independent variable. The cause that researchers change to study its effects.
Answer: Use context to map each term to its role in the claim or mechanism. Focus on function rather than memorizing scientific vocabulary.
Answer: Viewpoint 2. Independence means Y doesn't change regardless of X values.
Answer: Use context to map each term to its role in the claim or mechanism. Focus on function rather than memorizing scientific vocabulary.
Answer: To act as a control to measure treatment effects. Inactive treatment allows measurement of real effects.
Answer: Failing to reject a false null hypothesis. False negative - missing a real effect.
Answer: Null result. When data doesn't support the predicted outcome.
Answer: Uncontrolled experiment. Lacks comparison group to isolate variables.
Answer: As X increases, Y increases. Positive correlation means variables move in the same direction.
Answer: Analysis of variance. Compares multiple groups to identify differences.
Answer: The experimental results, graphs, and tables in the passage. Actual data trump theoretical claims when they conflict.
Answer: Replication of experiments. Independent repetition confirms the original findings are valid.
Answer: Data that does not fit expected patterns. Unexpected results that don't match predicted outcomes.
Answer: To evaluate the validity of each viewpoint. Comparing helps identify which explanations are supported by evidence.
Answer: Y does not depend on X. Constant Y regardless of X shows no dependence relationship.