TEAS 7 · Science · 5 min read
Scientific Reasoning: Experiments, Variables and Measurement
- Differentiate between independent, dependent, controlled, and confounding variables, and explain the functions of control groups and blinding in experimental design.
- Distinguish between scientific hypotheses, null and alternative hypotheses, scientific theories, and scientific laws while interpreting quantitative and qualitative data.
- Apply the metric system base units, prefixes, and laboratory measurement tools while maintaining accuracy, precision, and proper measurement techniques.
Formulating Hypotheses and Evaluating Scientific Data
Scientific inquiry often begins with an observation or question, followed by a testable hypothesis. A hypothesis is a tentative, testable, and falsifiable statement predicting the relationship between variables. When designing an investigation, researchers frame their predictions using two distinct hypotheses: the null hypothesis and the alternative hypothesis. The null hypothesis states that there is no effect of the independent variable on the dependent variable or no difference between the groups being compared. Conversely, an alternative hypothesis states that the independent variable affects the dependent variable or that a difference exists between the groups being compared.
During an investigation, researchers collect data to test these predictions. Quantitative data consists of numerical measurements and counts that can be analyzed statistically. Qualitative data consists of non-numerical, descriptive observations such as color, texture, or appearance. In any data set, researchers must watch for an outlier, which is a data point that differs markedly from other observations in a data set. Experimental conclusions must be drawn directly from empirical evidence gathered during the investigation. When analyzing patterns, researchers must remember that correlation between two variables demonstrates an association but does not establish a cause-and-effect relationship.
Over time, evidence gathered from multiple investigations builds broader scientific understanding. A scientific hypothesis can be supported or rejected by data, but it can never be proven with absolute certainty. An extensively tested, broad explanation of natural phenomena supported by a large body of evidence is known as a scientific theory. In contrast, a scientific law describes a consistent pattern or relationship in nature under specified conditions, often expressed mathematically. Peer review involves independent experts evaluating a study's methods, results, and conclusions, often before publication; peer review alone does not establish that findings are accepted by the broader scientific community.
Common mistakes
- Assuming that correlation establishes causation: A correlation demonstrates an association between variables but does not prove a cause-and-effect relationship.
- Confusing accuracy with precision: Accuracy measures how close a value is to the true or accepted reference value, whereas precision measures the closeness of agreement among repeated measurements under identical conditions.
- Believing that a scientific hypothesis can be proven true with absolute certainty: Data can support or reject a hypothesis, but it can never prove it with absolute certainty.
- Using beakers or Erlenmeyer flasks for high-precision volume measurements: A graduated cylinder is more precise than a beaker or Erlenmeyer flask, and a volumetric pipette or micropipette is required for delivering highly accurate, small volumes.
Key points
- In a simple controlled experiment, the experimenter manipulates one independent variable (horizontal x-axis), measures the dependent variable (vertical y-axis), and maintains controlled variables as constants across all groups.
- Control groups establish a baseline: negative controls are expected not to produce a response to reveal contamination or false positives, whereas positive controls verify that the assay works by producing a known response.
- Experimental bias is reduced using placebos, single-blind studies, double-blind studies, and random assignment, while replication and larger sample sizes minimize random error and individual variation.
- Hypotheses are testable and falsifiable predictions that are supported or rejected rather than proven; theories offer broad, extensively tested explanations, while laws describe consistent patterns under specified conditions.
- The metric system is decimal-based; the seven SI base units are the meter, kilogram, second, kelvin, mole, ampere, and candela, and metric prefixes indicate powers of ten.
- Laboratory measurement tools must match the required precision: graduated cylinders, volumetric pipettes, and micropipettes measure liquid volume more precisely than beakers or flasks, while balances measure mass and spring scales measure weight in newtons.
- Reading liquid volume requires viewing the meniscus at eye level (reading the bottom for most liquids, or the top if convex) to prevent parallax error.
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