Anyone familiar with graphical analysis?

  • Thread starter L²Cc
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In summary, the uncertainty for the sum of the masses is due to inconsistency in time measurements, and there is a large deviation between the average time and the smallest time measurement.
  • #1
L²Cc
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After having typed in the absolute uncertainties for my values, I get error bars that stretch across the graph, when my uncertainties are rather small compared to the initial value. What am I doing wrong?! Should I change the error bars to percentage or keep it at fixed value? (Those who use this graphing software will understand me...hopefully). Thank you.
 
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  • #2
What are you plotting, i.e. what are the abscissa and ordinate, or rather what are the independent and dependent variables?

If the uncertainties are small with respect to the value, and the magnitude of the error bars are larger, then it would seem to be a miscalculation of the error bar magnitude. If the error bars stretch across the graph, but the magnitudes of the error bars are much less than the associated value, it could be that the range of the axis (axes) are too small.

See this page - http://www.ncsu.edu/labwrite/res/gt/gt-stat-home.html

This might be helpful - http://www.rit.edu/~uphysics/graphing/graphingpart1.html#errorbars
 
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  • #3
Hmmm. I have re-calculated the uncertainties...and I obtain the same results. Since this is an Atwood lab, I divide the sum of the relative uncertainties of time and distance by the acceleration value. For example, for situation 2, where the difference of the masses is constant, the acceleration value is 2.55 +/- 1.08 (this is quite big)...is my arithmetic incorrect? Also, for the masses, they have an uncertainty of .03 each. Thus, when I find the sum of the masses, I double the uncertainty. Then, when graphing, I have 1/m+m2 representing the x-axis which I convert to kilograms. So, would it be correct to divide 0.06 by 150 kilograms (for example) and then multiply the obtained value by 150 so to get the absolute uncertainty of the sum of the masses when it's in the denominator (argh, I'm sure you lost me by now...Well, I hope you understand the main parts!) Thank you. I think my error bars are big because our time measurements are inconsistent, and there is a great deviation between the average time and the smallest time measurement! argh!
 
  • #4
I'm sure you lost me by now...

er. yes...

What do you mean by "an uncertainly of 0.03 each"? Do you mean the uncertainty is 3% of the measured mass? Or an uncertainty of 0.03Kg?

If you show your complete calculation for one of two points, somebody might be able to help more. Using ESP to guess what you did is even harder than doing physics :smile:
 

1. What is graphical analysis?

Graphical analysis is a method used in scientific research to visually represent data and identify patterns or relationships between variables. It involves creating graphs, charts, or diagrams to present and interpret data.

2. Why is graphical analysis important in scientific research?

Graphical analysis is important because it allows researchers to quickly and easily identify trends and patterns in their data. It also helps to communicate complex information in a visual format, making it easier for others to understand and interpret the results.

3. What are some common types of graphs used in graphical analysis?

Some common types of graphs used in graphical analysis include bar graphs, line graphs, scatter plots, and pie charts. These graphs can be used to represent different types of data, such as categorical, continuous, or discrete data.

4. How do you determine which type of graph to use for your data?

The type of graph to use depends on the type of data and the research question being addressed. For example, if you want to compare values between groups, a bar graph would be appropriate. If you want to show changes over time, a line graph would be more suitable. It is important to choose a graph that best represents the data and helps to answer the research question.

5. Can graphical analysis be used in all fields of science?

Yes, graphical analysis can be used in all fields of science. It is a universal tool that is commonly used in biology, chemistry, physics, and other scientific disciplines to analyze and present data. However, the specific types of graphs and techniques used may vary depending on the field and the type of data being analyzed.

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