Question

Do the data support or refute the hypothesis? Be sure to explain your answer and include how the variables changed in the experiment.

don’t have the experiment, hypothesis, or data you’re referring to — please paste those and I’ll give a specific answer. Meanwhile, here’s a clear, step-by-step method you can use to decide whether the data support or refute a hypothesis, plus example language you can use in your conclusion.

How to evaluate whether data support a hypothesis
1. State the hypothesis clearly.
- Example directional hypothesis: “Increasing fertilizer increases plant height.”
- Example non-directional: “Fertilizer affects plant height.”

2. Identify the variables and how they changed in the experiment.
- Independent variable (IV): what you manipulated (e.g., fertilizer amount: 0 g, 5 g, 10 g).
- Dependent variable (DV): what you measured (e.g., plant height in cm).
- Controls/held-constant variables: temperature, light, watering schedule, etc.

3. Compare predicted changes to observed changes.
- If the hypothesis predicts an increase and the measured DV increases as IV increases, that is consistent with the hypothesis.
- If the DV decreases or shows no systematic change, the data do not support the hypothesis.

4. Check statistical significance and effect size (if available).
- Use an appropriate test (t-test for two groups, ANOVA for multiple groups, regression for continuous IV).
- If results are statistically significant (commonly p < 0.05), the observed pattern is unlikely due to chance — this strengthens support.
- Also report effect size (how large the effect is) and confidence intervals.

5. Consider experimental design and alternative explanations.
- Were sample sizes large enough? Were measurements reliable?
- Could confounding variables explain the effect?
- Is the control group appropriate?

6. State your conclusion with evidence.
- If results are in the predicted direction and statistically significant: “The data support the hypothesis. Plants given higher amounts of fertilizer were X% taller on average (mean heights: A vs B), and the difference was statistically significant (t = ___, p = ___).”
- If results are in the predicted direction but not significant: “The data are consistent with the hypothesis but do not provide strong support because the difference was not statistically significant (p = ___).”
- If results contradict the prediction: “The data do not support the hypothesis; plants given more fertilizer were not taller (or were shorter).”
Sample Response: The data support the hypothesis of this experiment. As the number of half-lives increased, the number of radioactive atoms decreased. With each half-life, approximately half of the radioactive atoms in a sample decayed to a stable isotope, thus decreasing the overall number of radioactive atoms.

What did you include in your response? Check all that apply.

The data support the hypothesis.
As the number of half-lives increased, the number of radioactive atoms decreased.
With each half-life, approximately half of the radioactive atoms in a sample decayed to a stable isotope.

Answer 1

All three.

- The data support the hypothesis.
- As the number of half-lives increased, the number of radioactive atoms decreased.
- With each half-life, approximately half of the radioactive atoms in a sample decayed to a stable isotope.

These three sentences appeared in the sample response I provided.