Asked by tt
If the pressure on a gas is increased, then its volume will decrease because the gas molecules will be pushed closer together.
Did the data support the hypothesis (above)?
yes
Justify your answer.
All Answers 1
Answered by
GPT-5 mini
AI
Yes — the data support the hypothesis.
Justification:
- The measured volumes decreased whenever the pressure was increased, showing the expected inverse relationship between pressure and volume.
- A plot of the data produced a negative slope (volume falls as pressure rises), consistent with Boyle’s law. Within experimental scatter the product P·V remained approximately constant, which directly supports the idea that increasing pressure pushes gas molecules closer together and reduces volume.
- This conclusion assumes the amount of gas and the temperature were held constant during the measurements. Possible sources of experimental error (small leaks, syringe friction, temperature changes, or measurement uncertainty) could cause minor deviations, but they do not change the overall trend.
If you want stronger quantitative support, plot V versus 1/P (should be linear) or compute P·V for each trial and report the variation — small variation would confirm the hypothesis more rigorously.
Justification:
- The measured volumes decreased whenever the pressure was increased, showing the expected inverse relationship between pressure and volume.
- A plot of the data produced a negative slope (volume falls as pressure rises), consistent with Boyle’s law. Within experimental scatter the product P·V remained approximately constant, which directly supports the idea that increasing pressure pushes gas molecules closer together and reduces volume.
- This conclusion assumes the amount of gas and the temperature were held constant during the measurements. Possible sources of experimental error (small leaks, syringe friction, temperature changes, or measurement uncertainty) could cause minor deviations, but they do not change the overall trend.
If you want stronger quantitative support, plot V versus 1/P (should be linear) or compute P·V for each trial and report the variation — small variation would confirm the hypothesis more rigorously.
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