Research methodology
61 flashcards covering Research methodology for the ACT Science section.
Research methodology is the structured process scientists use to design and conduct studies, collect data, and draw reliable conclusions. It involves steps like forming hypotheses, selecting methods for gathering evidence, and analyzing results to ensure accuracy and avoid bias. This approach is essential for producing trustworthy scientific knowledge, helping us understand everything from biology to physics.
On the ACT Science section, research methodology often appears in questions about experimental design, data interpretation, and evaluating studies. You'll encounter passages with graphs, tables, or descriptions of experiments, where you might need to identify independent and dependent variables, recognize flaws like sampling errors, or determine if results support a hypothesis. Common traps include mistaking correlation for causation or overlooking controls, so focus on critically assessing how studies are set up and what the data really shows.
Practice identifying key elements in experiments to boost your accuracy.
Terms (61)
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Scientific Method
The scientific method is a systematic process used by scientists to investigate natural phenomena, involving steps such as making observations, forming a hypothesis, conducting experiments, and analyzing data to draw conclusions.
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Hypothesis
A hypothesis is a testable statement or prediction that serves as a starting point for an investigation, proposing a possible explanation for an observed phenomenon based on prior knowledge or observations.
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Theory
A theory in science is a well-substantiated explanation of some aspect of the natural world that is based on a body of facts that have been repeatedly confirmed through observation and experiment.
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Independent Variable
The independent variable is the factor in an experiment that is deliberately changed or manipulated by the researcher to observe its effect on the outcome.
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Dependent Variable
The dependent variable is the factor in an experiment that is measured or observed to see how it responds to changes in the independent variable.
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Controlled Variable
A controlled variable is a factor in an experiment that is kept constant to ensure that it does not influence the outcome, allowing for a fair test of the relationship between the independent and dependent variables.
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Control Group
The control group in an experiment is a group that does not receive the treatment or variable being tested, serving as a baseline for comparison with the experimental group.
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Experimental Group
The experimental group is the group in an experiment that is exposed to the independent variable or treatment being tested, allowing researchers to observe its effects.
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Sample Size
Sample size refers to the number of individuals or items selected from a population for a study, with larger sizes generally providing more reliable results by reducing the impact of random variation.
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Random Sampling
Random sampling is a method of selecting participants for a study where each member of the population has an equal chance of being chosen, helping to minimize bias and make results more representative.
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Bias in Research
Bias in research occurs when the design, conduct, or analysis of a study systematically favors certain outcomes, often due to flaws in sampling, measurement, or interpretation.
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Confounding Variable
A confounding variable is an extraneous factor that correlates with both the independent and dependent variables, potentially distorting the results by making it hard to determine cause and effect.
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Correlation
Correlation describes a statistical relationship between two variables, indicating how one changes in relation to the other, but it does not imply that one causes the other.
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Causation
Causation means that one event directly causes another, requiring evidence from controlled experiments that show changes in one variable directly produce changes in another.
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Mean
The mean is the average of a set of numbers, calculated by adding all the values together and dividing by the total number of values, providing a measure of central tendency.
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Median
The median is the middle value in a list of numbers arranged in order, which represents the central tendency and is less affected by outliers than the mean.
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Mode
The mode is the value that appears most frequently in a data set, serving as a measure of central tendency that highlights the most common occurrence.
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Range
The range is the difference between the highest and lowest values in a data set, providing a simple measure of the spread or variability of the data.
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Standard Deviation
Standard deviation measures how spread out the values in a data set are from the mean, calculated as the square root of the variance, indicating the data's dispersion.
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Bar Graph
A bar graph is a chart that uses rectangular bars to represent data, with the length of each bar corresponding to the value of the data category it represents.
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Line Graph
A line graph displays data points connected by lines, typically used to show trends or changes over time, making it easy to visualize relationships.
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Pie Chart
A pie chart is a circular graph divided into slices to illustrate numerical proportions, with each slice representing a percentage or fraction of the whole.
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Scatter Plot
A scatter plot is a graph that uses dots to represent the relationship between two variables, helping to identify patterns, trends, or correlations in the data.
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Trend in Data
A trend in data refers to a general direction or pattern observed over time or across variables, such as increasing, decreasing, or remaining constant.
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Interpolation
Interpolation is the process of estimating a value within the range of a data set by assuming a pattern or trend based on existing data points.
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Extrapolation
Extrapolation is the process of estimating values outside the range of a data set by extending the observed trend, though it can be less accurate due to potential changes beyond the data.
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Direct Proportion
Direct proportion means that two quantities increase or decrease at the same rate, so as one increases, the other increases by a constant multiple.
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Inverse Proportion
Inverse proportion occurs when one quantity increases as another decreases, such that their product remains constant, like speed and time for a fixed distance.
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Positive Correlation
Positive correlation is when both variables increase or decrease together, meaning as one goes up, the other tends to go up as well.
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Negative Correlation
Negative correlation is when one variable increases as the other decreases, indicating an inverse relationship between the two.
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Validity of an Experiment
The validity of an experiment refers to the extent to which it accurately measures what it intends to, free from errors that could affect the results.
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Reliability of Data
Reliability of data means that the results are consistent and reproducible under the same conditions, indicating that the measurement methods are stable.
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Replication of Experiments
Replication involves repeating an experiment to verify results, ensuring that findings are not due to chance and increasing confidence in the conclusions.
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Peer Review
Peer review is the process where experts in the field evaluate a study before publication, helping to ensure the quality, accuracy, and credibility of the research.
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Observation
Observation is the act of gathering data by watching and recording phenomena without manipulating variables, forming the basis for scientific inquiry.
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Inference
An inference is a conclusion drawn from evidence and reasoning, going beyond direct observations to explain patterns or causes.
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Qualitative Data
Qualitative data consists of non-numerical information that describes qualities or characteristics, such as colors or textures, often gathered through observations.
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Quantitative Data
Quantitative data is numerical information that can be measured and analyzed statistically, allowing for precise comparisons and calculations.
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Hypothesis Testing
Hypothesis testing is a method used to determine if there is enough evidence in the data to reject a null hypothesis in favor of an alternative one.
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Null Hypothesis
The null hypothesis is a statement that assumes no effect or no difference exists, serving as the default position that is tested against in an experiment.
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Alternative Hypothesis
The alternative hypothesis is a statement that proposes an effect or difference does exist, representing what the researcher aims to support with evidence.
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Experiment Design
Experiment design is the planning process that outlines the procedures, variables, and controls to ensure the study can answer the research question effectively.
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Survey Method
The survey method involves collecting data from a group of people through questionnaires or interviews to gather information about opinions, behaviors, or characteristics.
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Double-Blind Study
A double-blind study is a research design where neither the participants nor the researchers know who is receiving the treatment, reducing bias in the results.
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Placebo Effect
The placebo effect occurs when participants experience changes due to their belief in a treatment, even if it is inactive, highlighting the role of psychological factors.
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Random Assignment
Random assignment is the process of placing participants into groups by chance, ensuring that each group is comparable and minimizing selection bias.
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Stratified Sampling
Stratified sampling is a technique where the population is divided into subgroups based on characteristics, and samples are taken from each to ensure representation.
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Common Trap: Confusing Correlation and Causation
A common trap in research is assuming that because two variables are correlated, one must cause the other, when other factors could be involved.
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Strategy for Identifying Variables
A strategy for identifying variables is to determine which factor is being changed (independent), which is being measured (dependent), and which are kept constant (controlled).
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Example: Controlled Experiment
In a controlled experiment testing plant growth, watering one group with fertilizer and another with water while keeping light and soil the same shows the effect of the fertilizer.
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Formula: Calculating Mean
The formula for calculating the mean is to sum all values in a data set and divide by the number of values, providing a central value for analysis.
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Worked Example: Interpreting a Graph
In a line graph showing temperature over time, an upward trend indicates increasing temperatures, which could be used to infer seasonal changes.
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Population in Research
The population in research is the entire group of individuals or items that the study aims to draw conclusions about, from which a sample is selected.
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Data Analysis
Data analysis involves examining and interpreting collected data to identify patterns, draw conclusions, and support or refute hypotheses.
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Ethical Considerations
Ethical considerations in research include ensuring participant safety, informed consent, and avoiding harm, which are essential for valid and responsible studies.
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Longitudinal Study
A longitudinal study observes the same subjects over an extended period to track changes, providing insights into long-term effects or developments.
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Cross-Sectional Study
A cross-sectional study collects data from a population at a single point in time, offering a snapshot to compare different groups or variables.
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Reliable Source
A reliable source in research is one that is credible, based on evidence, and peer-reviewed, ensuring the information is accurate and trustworthy.
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Experimental Error
Experimental error refers to inaccuracies in measurements or procedures that can affect results, and identifying them helps improve the study's validity.
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Graph Scale
Graph scale is the range and intervals on the axes of a graph, which must be appropriate to accurately represent the data without misleading interpretation.
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Outlier in Data
An outlier is a data point that differs significantly from others in the set, potentially indicating errors or unique conditions that need further investigation.