How can I calculate uncertainty in my lab report data?

In summary, the conversation discusses calculating uncertainty for a lab report and the use of the square root rule. The uncertainty is typically determined by the measurement tool or process, but the square root rule can be applied if no other information is available. The uncertainty in the given example is calculated as ##\sqrt{2 CPM}##.
  • #1
Hayool
14
0
Hi,

I'm doing a lab report and for every number we need to calculate the uncertainty. I tried to calculate by using the SQRT of the number but i didn't get the same answer as my partner had?
could you help me!

These are the numbers and the uncertainty of my partner which i could not figure out how it was done!

upload_2016-3-1_14-1-27.png
 
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  • #2
It appears the uncertainty was calculated as
##\sqrt{2CPM}##.
 
  • #3
RUber said:
It appears the uncertainty was calculated as
Thanks RUber for the fast reply.

Are there any other way to calculate the uncertainty ?
And how can i know I'm using that right way?
 
  • #4
Normally, the uncertainty comes from your measurement tool, or from the process itself.
Without more information about the expected relationships between your data, I am not sure why you would choose one method over another for uncertainty estimation.

In this document (http://instructor.physics.lsa.umich.edu/int-labs/Statistics.pdf) there is a reference to the "square root rule," which generally says if you know nothing else about a number (large integer), the standard deviation is the square root of the number.

Assuming CPM is a measure of some C per minute, then it might make sense that your count for 2 minutes was 2*CPM.
Then the uncertainty in that measurement would be (using square root rule) ##\sqrt{2 CPM}##.
 

What is uncertainty calculation?

Uncertainty calculation is a process used in science to estimate the possible errors or variations in measurements or experimental data. It helps to quantify the level of confidence or reliability in the results obtained from an experiment.

Why is uncertainty calculation important in scientific research?

Uncertainty calculation is important because it allows scientists to understand the limitations of their measurements and results. It helps to evaluate the precision and accuracy of data, which is crucial for drawing valid conclusions and making informed decisions.

What are the types of uncertainties that can be calculated?

There are two main types of uncertainties - random and systematic. Random uncertainties arise from natural variations in measurements, while systematic uncertainties result from flaws or biases in the experimental setup or equipment. Both types of uncertainties can be calculated and combined to determine the overall uncertainty in the results.

How is uncertainty calculated?

Uncertainty is calculated using statistical methods, such as standard deviation or confidence intervals. These methods take into account the variability and distribution of data points to estimate the range of possible values for the true measurement or result.

How can uncertainty be reduced in scientific experiments?

Uncertainty can be reduced by improving the precision and accuracy of measurements. This can be achieved by using more sensitive and calibrated equipment, increasing the sample size, and repeating experiments multiple times. It is also important to identify and minimize sources of systematic errors in the experimental setup.

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