ACT · Science58 flashcards

Comparing experiments

58 flashcards covering Comparing experiments for the ACT Science section.

Comparing experiments is about analyzing two or more scientific studies or tests side by side to spot differences in their setup, procedures, and results. This helps you understand how changes in variables—like temperature or materials—affect outcomes and allows you to evaluate which experiment provides stronger evidence for a hypothesis. It's a key skill in science because it reveals the strengths and weaknesses of research methods, leading to more reliable conclusions.

On the ACT Science section, comparing experiments shows up in questions that ask you to interpret data from graphs, tables, or descriptions and decide how variations between experiments impact findings. Common question types include identifying conflicting results or determining which study best controls for variables, with traps like overlooking subtle differences in conditions or misreading trends. Focus on noting independent and dependent variables, sample sizes, and controls to avoid errors and select the correct answer.

Always start by listing the key differences in experimental design.

Terms (58)

  1. 01

    Independent Variable

    The factor that is deliberately changed in an experiment to test its effect on the outcome.

  2. 02

    Dependent Variable

    The factor that is measured or observed in an experiment to see how it responds to changes in the independent variable.

  3. 03

    Control Group

    The group in an experiment that does not receive the treatment or variable being tested, serving as a baseline for comparison.

  4. 04

    Experimental Group

    The group in an experiment that receives the treatment or variable being tested, allowing comparison with the control group.

  5. 05

    Controlled Variables

    The factors kept constant across all groups in an experiment to ensure that only the independent variable affects the dependent variable.

  6. 06

    Hypothesis

    A testable prediction about the relationship between variables in an experiment, often stated as an if-then statement.

  7. 07

    Replication

    The process of repeating an experiment multiple times or in different settings to verify the reliability of the results.

  8. 08

    Sample Size

    The number of subjects or trials in an experiment, where a larger size generally reduces the impact of random variation on results.

  9. 09

    Mean

    The average value of a data set, calculated by summing all values and dividing by the number of values, useful for comparing central tendencies.

  10. 10

    Median

    The middle value in a data set when ordered from least to greatest, providing a measure of central tendency that is less affected by outliers.

  11. 11

    Range

    The difference between the highest and lowest values in a data set, indicating the spread of data when comparing experiments.

  12. 12

    Trend in Data

    The general pattern or direction shown by data points in a graph, such as increasing or decreasing, when analyzing multiple experiments.

  13. 13

    Positive Correlation

    A relationship between two variables where an increase in one is associated with an increase in the other, as seen in comparative data analysis.

  14. 14

    Negative Correlation

    A relationship between two variables where an increase in one is associated with a decrease in the other, often compared across experiments.

  15. 15

    Confounding Variable

    An extraneous factor that influences the dependent variable and can obscure the relationship between the independent and dependent variables in experiments.

  16. 16

    Bias in Experiments

    A systematic error introduced during experiment design or data collection that skews results, making fair comparisons between studies difficult.

  17. 17

    Random Error

    Variation in results due to unpredictable factors, which can be assessed by comparing repeated trials within an experiment.

  18. 18

    Systematic Error

    A consistent inaccuracy in measurements that affects all data in the same way, potentially leading to incorrect comparisons between experiments.

  19. 19

    Graph Interpretation

    The process of analyzing graphs from different experiments to identify patterns, differences, or relationships between variables.

  20. 20

    Table Comparison

    Examining data tables from multiple experiments to spot similarities, differences, or trends in the values of key variables.

  21. 21

    Percentage Difference

    A way to measure how much two values from different experiments differ relative to their sizes, calculated as the absolute difference divided by the average.

  22. 22

    Rate of Change

    The speed at which a dependent variable changes with respect to the independent variable, often compared by calculating slopes in line graphs.

  23. 23

    Slope of a Line

    The steepness of a line on a graph, representing the rate of change, which can be compared between experiments to assess variable relationships.

  24. 24

    Intersection Point

    The point where lines from different experiments on the same graph cross, indicating where variables have equal values.

  25. 25

    Area Under the Curve

    The space beneath a curve on a graph, which can represent quantities like total change and be compared between experiments for insights.

  26. 26

    Experimental Controls

    The measures taken to minimize the effects of extraneous variables, ensuring that comparisons between experiments are valid and reliable.

  27. 27

    Validity of an Experiment

    The extent to which an experiment accurately tests what it intends to, which must be evaluated when comparing results from different studies.

  28. 28

    Reliability of Data

    The consistency of results when an experiment is repeated, a key factor in determining how trustworthy comparisons between experiments are.

  29. 29

    Extrapolation

    Extending a trend line beyond the data points to predict outcomes, though it carries risks of inaccuracy when comparing to actual experimental results.

  30. 30

    Interpolation

    Estimating values between known data points on a graph, useful for comparing intermediate results from different experiments.

  31. 31

    Anomalous Data Point

    A data point that deviates significantly from the expected trend, which may indicate errors and affect comparisons between experiments.

  32. 32

    Standard Deviation

    A measure of the spread of data around the mean, helping to assess variability when comparing results from multiple experiments.

  33. 33

    Normal Distribution

    A bell-shaped curve where data clusters around the mean, allowing for comparisons of data spreads in different experiments.

  34. 34

    Strategy for Comparing Averages

    A method to evaluate means from different experiments by considering sample sizes and contexts to determine if differences are meaningful.

  35. 35

    Identifying Trends

    A technique for spotting patterns in data from various experiments, such as using visual aids to compare increases or decreases.

  36. 36

    Evaluating Evidence

    Assessing whether data from one experiment supports or contradicts another by examining variables and outcomes for consistency.

  37. 37

    Contradictory Results

    Findings from different experiments that do not agree, requiring analysis of possible causes like differing conditions or errors.

  38. 38

    Sources of Error

    Factors that lead to inaccurate results in experiments, such as measurement mistakes, which must be identified when making comparisons.

  39. 39

    Improving Experiments

    Modifying experimental design, like increasing sample size or controlling variables better, to enhance the accuracy of comparisons.

  40. 40

    Double-Blind Procedure

    A method where neither participants nor researchers know who receives the treatment, reducing bias in comparisons between groups.

  41. 41

    Placebo

    An inactive substance given to the control group to mimic the treatment, allowing for fair comparison of effects in experiments.

  42. 42

    Random Assignment

    The process of assigning subjects to groups by chance, ensuring that comparisons between experimental and control groups are unbiased.

  43. 43

    Longitudinal Study

    An experiment that observes subjects over a long period, which can be compared to cross-sectional studies for insights into changes over time.

  44. 44

    Cross-Sectional Study

    An experiment that analyzes data from a population at a single point in time, useful for quick comparisons with other study types.

  45. 45

    Cause and Effect

    The relationship where one variable directly influences another, which must be established when comparing experimental outcomes.

  46. 46

    Scatterplot Analysis

    Examining a graph of points to determine relationships between variables, such as correlations, when comparing data from experiments.

  47. 47

    Line of Best Fit

    A straight line drawn through scatterplot data to show the overall trend, aiding in comparisons between different experiments.

  48. 48

    Bar Graph Comparison

    Using bar graphs from multiple experiments to visually compare the heights of bars, representing different variable levels.

  49. 49

    Frequency Distribution

    A summary of how often values occur in a data set, helpful for comparing the distribution of results across experiments.

  50. 50

    Mode

    The most frequently occurring value in a data set, which can be compared between experiments to identify common outcomes.

  51. 51

    Quartiles

    The values that divide a data set into four equal parts, allowing for comparison of data spreads in different experiments.

  52. 52

    Box-and-Whisker Plot

    A graph that shows the median, quartiles, and range of data, facilitating visual comparisons between experimental results.

  53. 53

    Hypothesis Rejection

    The decision to discard a hypothesis based on data that does not support it, often compared across multiple experiments.

  54. 54

    Falsifiability

    The quality of a hypothesis that allows it to be tested and potentially proven wrong, essential for valid comparisons in science.

  55. 55

    Peer Review

    The evaluation of experimental results by other scientists to ensure accuracy, which supports reliable comparisons between studies.

  56. 56

    Scientific Method

    A systematic process of observation, hypothesis, experimentation, and analysis, used as a framework for comparing investigations.

  57. 57

    Variable Isolation

    The technique of controlling all variables except one to clearly observe its effect, improving accuracy in experimental comparisons.

  58. 58

    Comparative Analysis

    The overall process of examining similarities and differences between experiments to draw conclusions about variables and results.