Key Takeaways
- The scientific method: observation → question → hypothesis → experiment → analysis → conclusion
- Independent variable is manipulated; dependent variable is measured; controlled variables are kept constant
- Control groups provide a baseline; randomization and blinding reduce bias
- Correlation does not prove causation—look for confounding variables
- Evaluate studies by checking sample size, control groups, and potential bias
Scientific Reasoning and the Scientific Method
The TEAS tests your ability to understand scientific investigation, interpret experimental data, and apply critical thinking to scientific questions.
The Scientific Method
The scientific method is a systematic approach to inquiry:
| Step | Description | Example |
|---|---|---|
| 1. Observation | Notice a phenomenon | Patients with low vitamin D report fatigue |
| 2. Question | Ask why or how | Does vitamin D supplementation reduce fatigue? |
| 3. Hypothesis | Propose a testable explanation | If patients take vitamin D, then fatigue will decrease |
| 4. Experiment | Test the hypothesis | Randomized controlled trial |
| 5. Analyze Data | Examine results statistically | Compare fatigue scores between groups |
| 6. Conclusion | Support or refute hypothesis | Evidence supports/does not support hypothesis |
| 7. Communicate | Share findings | Publish in peer-reviewed journal |
Variables in Experiments
| Variable Type | Definition | Example |
|---|---|---|
| Independent | What researcher changes/manipulates | Vitamin D dose |
| Dependent | What researcher measures (outcome) | Fatigue score |
| Controlled | Kept constant to ensure fair test | Age, diet, sleep |
| Confounding | Uncontrolled variable affecting results | Exercise level |
Experimental Design
| Component | Purpose |
|---|---|
| Control group | Baseline for comparison (no treatment) |
| Experimental group | Receives the treatment |
| Randomization | Reduces selection bias |
| Blinding | Participants don't know their group |
| Double-blind | Neither participants nor researchers know |
| Placebo | Inactive treatment for control group |
| Sample size | Larger = more reliable results |
Types of Studies
| Type | Description | Strength |
|---|---|---|
| Experimental | Researcher manipulates variables | Can show causation |
| Observational | Researcher only observes | Cannot prove causation |
| Case study | In-depth study of one subject | Detailed but not generalizable |
| Survey | Collects self-reported data | Quick, large samples |
| Longitudinal | Follows subjects over time | Shows change/development |
Correlation vs. Causation
Correlation: Two variables are related Causation: One variable directly causes the other
Key point: Correlation does NOT prove causation.
Example: Ice cream sales and drowning deaths are correlated (both increase in summer), but ice cream does not cause drowning. The confounding variable is hot weather.
Reading Data and Graphs
Tables: Organize data in rows and columns
- Identify what each column represents
- Look for patterns and trends
Line graphs: Show change over time
- X-axis usually shows time
- Look for increases, decreases, peaks
Bar graphs: Compare categories
- Compare heights of bars
- Identify largest/smallest
Scatter plots: Show relationships
- Positive correlation: dots trend upward
- Negative correlation: dots trend downward
- No correlation: random scatter
Data Analysis Concepts
| Concept | Meaning |
|---|---|
| Mean | Average value |
| Range | Difference between highest and lowest |
| Outlier | Data point far from others |
| Trend | General direction of data |
| Statistical significance | Results unlikely due to chance |
Reliability and Validity
| Term | Definition |
|---|---|
| Reliability | Consistency of results when repeated |
| Validity | Accuracy—does it measure what it claims? |
| Precision | How close measurements are to each other |
| Accuracy | How close measurements are to true value |
Interpreting Scientific Claims
Questions to ask:
- What is the sample size?
- Was there a control group?
- Could there be confounding variables?
- Can the results be replicated?
- Is the source credible?
- Has it been peer-reviewed?
Common Scientific Reasoning Errors
| Error | Description |
|---|---|
| Confirmation bias | Seeking only evidence that supports beliefs |
| Small sample size | Drawing conclusions from too few subjects |
| Assuming causation | Concluding cause from correlation only |
| Overgeneralization | Applying results too broadly |
| Cherry-picking | Selecting only favorable data |
In an experiment testing a new medication, what is the purpose of the control group?
A researcher finds that students who eat breakfast have higher test scores. Can the researcher conclude that eating breakfast causes higher scores?
Which variable does the researcher manipulate in an experiment?