Putting uncertainty on a scatter

  • Thread starter PythagoreLove
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In summary, the conversation is about creating a scatter plot with average numerical data and adding standard deviation to it. The person plans to use MatLab and a function called errorbar and herrorbar for the horizontal and vertical error bars.
  • #1
PythagoreLove
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Hi, first of all, sorry if my English is not perfect I'm from Quebec City and English is not my first language.

I'm trying to make a scatter plot with average of numerical data. But now I also want to put the standard deviation on the scatter.

Exemple, I have a point (x,[y ± σ]) and I want to have a point on my coordinate (x,y) and a line that goes to x - σ to x + σ. Thank you


PythagoreLove
 
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  • #2
Sorry I forgot to say, I need vertical and horizontal error bars
 
  • #3
What tool do you want to use to produce this?
 
  • #4
Sorry I finally got it, I was working on MatLab and I used the function errorbar and a function made by a user called herrorbar for my horizontal
 
  • #5
,

Thank you for your question. Adding uncertainty to a scatter plot can be a useful way to visualize the variability in your data. To do this, you can plot each data point with its corresponding standard deviation as you mentioned. This will give you a point on your coordinate (x,y) and a line that extends from x - σ to x + σ. This will help to show the range of values for each data point and give a better understanding of the overall variability in your data set. Additionally, you can also consider using error bars to represent the uncertainty, which would be a vertical line extending from each data point to the upper and lower bounds of the standard deviation. This can make it easier to compare the variability between different data points. I hope this helps and best of luck with your scatter plot!
 

Related to Putting uncertainty on a scatter

1. How can uncertainty be represented on a scatter plot?

Uncertainty can be represented on a scatter plot by using error bars, which are lines or shaded areas that show the range of values within which the data points are likely to fall. These error bars can be drawn vertically or horizontally, depending on the nature of the data.

2. What is the purpose of adding uncertainty to a scatter plot?

Adding uncertainty to a scatter plot allows for a more accurate and comprehensive visualization of the data. It helps to convey the level of variation or precision in the measurements and can aid in identifying any trends or patterns in the data.

3. How is uncertainty calculated and added to a scatter plot?

Uncertainty is typically calculated by taking into account the standard deviation or confidence interval of the data. Once calculated, the error bars can be added to the scatter plot by extending the data points or by using a separate data series specifically for the error bars.

4. How do different types of uncertainty affect a scatter plot?

There are different types of uncertainty, such as random and systematic, that can affect a scatter plot differently. Random uncertainty can result in data points that are more spread out, while systematic uncertainty can cause a bias in the data. It is important to consider and account for these different types of uncertainty when interpreting a scatter plot.

5. Are there any limitations to representing uncertainty on a scatter plot?

While representing uncertainty on a scatter plot can provide valuable information, it is important to note that it is not always possible to accurately capture all sources of uncertainty. Additionally, the representation of uncertainty on a scatter plot may vary depending on the data and the methods used to calculate it.

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