Proving a dependence between variables

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In summary, the conversation discussed finding the relationship between ##\psi## and ##\gamma## using the equation $$\Lambda=\sqrt{\gamma ^2+4 \pi ^2 \psi ^2} \sum _{j=0}^{\infty } \frac{\left(\frac{(2 j-1)\text{!} (2 \pi \psi )^j}{(2 j)\text{!} \left(\gamma ^2+4 \pi ^2 \psi ^2\right)^{j/2}}\right)^2}{1-2 j}$$ and attempted to find a closed form approximation by using the Taylor series of ##E(x)## but was unable to do
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MathsNewb
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Homework Statement



I want to find the relationship between ##\psi## and ##\gamma## from this equation
$$\Lambda=\sqrt{\gamma ^2+4 \pi ^2 \psi ^2} \sum _{j=0}^{\infty } \frac{\left(\frac{(2 j-1)\text{!} (2 \pi \psi )^j}{(2 j)\text{!} \left(\gamma ^2+4 \pi ^2 \psi ^2\right)^{j/2}}\right)^2}{1-2 j}$$ thereby proving a dependence between ##\psi## and ##\gamma## (where ##\psi##,##\gamma## and ##\Lambda## are variables)


Homework Equations



The above derives from $$\Lambda=\frac{2 \sqrt{\gamma ^2+4 \pi ^2 \psi ^2} E\left(\frac{4 \psi ^2 \pi ^2}{\gamma ^2+4 \pi ^2 \psi ^2}\right)}{\pi }$$

The Attempt at a Solution



Trying to find a closed form approximation.
 
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  • #2
I tried to find the Taylor series of ##E(x)## and substitute in the equation, however I was unable to obtain a closed form solution. Can anyone help? Thanks in advance.
 

Related to Proving a dependence between variables

1. How do you prove a dependence between variables?

To prove a dependence between variables, you need to conduct a statistical analysis. This involves collecting data, identifying the variables, and using a statistical test such as correlation or regression to determine the strength and direction of the relationship between the variables.

2. What is the purpose of proving a dependence between variables?

The purpose of proving a dependence between variables is to understand the relationship between two or more variables and to determine if changes in one variable have an impact on the other. This can help in making predictions, identifying patterns, and understanding the underlying mechanisms of a phenomenon.

3. What type of data is needed to prove a dependence between variables?

You will need quantitative data for both variables in order to prove a dependence between them. This means that the data should be in numerical form and can be measured or counted. Qualitative data, such as opinions or descriptions, cannot be used to prove a dependence between variables.

4. How do you interpret the results of a statistical test for dependence between variables?

The results of a statistical test will provide a value for the strength of the relationship between the variables, as well as the significance of that relationship. A positive value indicates a positive correlation, meaning that as one variable increases, the other also tends to increase. A negative value indicates a negative correlation, meaning that as one variable increases, the other tends to decrease. The significance value tells you if the relationship is statistically significant, meaning it is not due to chance.

5. What are some common mistakes when trying to prove a dependence between variables?

One common mistake is assuming that a correlation between two variables implies causation. Just because two variables are related does not necessarily mean that one causes the other. Other factors may be involved in the relationship. It is also important to use appropriate statistical tests and to ensure that the data is accurate and representative of the population being studied.

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