- Created by: Katie
- Created on: 07-07-13 12:24
State whether your reslts support the hypothesis that you made.
If your hypothesis was the higher the mass of calcium oxide powder added to the water, the higher the difference will be between the starting temperature and final temperature, say:
Yes my experiment supports my hypothesis as the higher the mass of calcium oxide powder added to the water, the higher the difference was between the starting temperature and the final temperature of the solution.
Give examples of your results that you gained from the experiment. For example:
In my experiment I gained the results of 2,4,7,8 and 10. When I plotted this on my graph I found that I had an anomaly in my results as the 7 didn't fit the pattern of the other results that were in a regular pattern of 2 so from this I can suspect that the 7 should have been a 6 degree change from the starting and ending temperature of the solution.
A example of an answer to this question would be:
Bt talking with other members of my class I would be able to see whether there were any regular patterns between results if I could not identify any from my results table and my graph. You would also be able to see whether you had any anomalies in your results. It would also reveal whether the results are reproducible.
Independant variable - just state the independent variable of your investigation.
When it asks you about the range of your independent variable make sure you state the units as well otherwise you wouldn't be able to get the mark.
When you talk about whether your range was suitable state whether you think it was a suitable range or why it wasn't and include enough detail and enough results so the examiner is able to see whether the range was suitable to investigate your hypothesis.
An example of this would be:
Yes it was a suitable range for my experiment as we were able to gather a wide range or results to how much each mass of calcium oxide would effect the temperature of the solution, for this we found that it ranged from a 2 degrees change (for the 1g of calcium oxide) to a 10 degrees change (for the 5g of calcium oxide). From this we were able to see a general pattern that occured for every time we increased the mass of calcium oxide by 1g.
Did you get any anomlies?
Yes I did gain one anomaly result, the series of results I gathered were 2, 4, 7, 8 and 10. When plotting this on the graph the result of 7, which I gained from adding 3g was an anomaly as it didn't fit into my line of best fit and it also didn't fit the regular trend or pattern of previous results.
If you did gain an anomaly:
- Identify the anomaly
- Why was it an anomaly?
If you didn't gain an anomaly:
- Identify your results
- What was the pattern of your results - positive/negative correlation, did it go up in 2s etc?
- How can you tell there were no anomalies? (look at your line of best fit on your graph)
Look at Case Study 1. Does it support the hypothesis given? Has it got any incorrect variables? Does it contain any anomalies (if it has is this included in the mean?) or has it got valid data?
Do this for both Case Study 2 and 3. If one contains an anomaly state the anomaly and where it occurs within the experiment and if it is included in the mean. If it measures the wrong variable, what does it measure instead? What should it measure?
For example: Case Study 1 supports the hypothesis as it investigates the correct variable with valid results. Case Study 2 has an anomaly (o.55 on a drop height of 0.90m on the 3rd repeat) which is then included in the mean, this makes the results inaccurate. Case Study 3 doesn't measure the drop height/m but the size of the ball that is being dropped, therefore, this is the wrong variable.
Look closely at Case Study 4 and identify anything similar to what you had to look for in the last question. However, they will not have given you a completly irrelevant case study. So try and style your answer like this:
Case study 4 investigates the wrong variable however, we can conclude that material E was a similar material to our measurement as when we dropped the ball at 1m the mean was o.74 and marterial E's mean bounce height/m was 0.76. Whereas, material A had a mean of 0.26m therefore, it wasn't as bouncy as the material I used. The hypothesis therefore, is affected by the material used as some gain more kenetic energy at the drop height of 1m due to the elastic coefficient, the lower the elastic coefficient, the lower the mean bounce height is.
Just like you did at the start of your ISA come up with a hypothesis, however, this time you have been given the data so you just need to identify the pattern that has occurred and come up with a hypothesis to support this.
Then explain how the data you have supports this hypothesis just like you did in a previous question, make sure you include data from the case study and justify why you think the hypothesis supports the data you have.