Independence from a variable - Graphical confusion

In summary, the conversation was about a graph where the magnitude, M, was found to depend on the number of points, N, even though it should not. The line of best fit was found to be M = a*N^b. The question was whether it was possible to remove the dependency of M on N and plot a graph where M = 3. The speaker was advised to provide a real life situation and practical goal for better advice.
  • #1
WMBM
1
0
http://postimg.org/image/pb0eu3ap3/
So I've got this graph, and magnitude, M, depends on the number of points, N,... but it shouldn't.
http://postimg.org/image/pb0eu3ap3/
The line of best fit is... M = a*N ^b

It's been a while since I studied, but knowing their relationship would it be possible to remove M's dependancy on N, i.e. in effort to plot a graph where e.g. M = 3?

Cheers Will
 
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  • #2
You aren't using language that has a specific mathematical interpretation. You'll get better advice if you describe the real life situation and say what practical goal you are trying to accomplish.
 

What is "Independence from a variable - Graphical confusion"?

Independence from a variable - Graphical confusion refers to the concept of ensuring that the outcome of one variable is not influenced by another variable. This is important in scientific research to accurately measure the effect of a specific variable on the outcome.

Why is it important to ensure independence from a variable in scientific research?

Ensuring independence from a variable is important because it allows researchers to accurately measure the effect of a specific variable on the outcome. Without independence, the results may be skewed and lead to incorrect conclusions.

How can graphical confusion affect research results?

Graphical confusion can affect research results by introducing bias and making it difficult to determine the true effect of a variable. It can also lead to incorrect conclusions and hinder the progress of scientific knowledge.

What are some methods to achieve independence from a variable in research?

One method is randomization, where participants are randomly assigned to different groups to ensure that any potential confounding variables are evenly distributed. Another method is controlling for variables by measuring and adjusting for their effects in the analysis.

How can researchers determine if there is independence from a variable in their data?

Researchers can use statistical tests, such as correlation analysis or regression analysis, to determine if there is a relationship between variables. They can also visually inspect graphs to look for patterns and relationships between variables.

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