Question on how to assure randomness for a set of dependent variables

In summary, the conversation discusses the need to obtain a set of variables that assures randomness in the output of a function. The central limit theorem is mentioned as a way to ensure randomness by adding random independent variables. However, the question arises when some of the variables are implicitly dependent on each other. The speaker is unsure of the proper approach and asks for suggestions, mentioning the use of random values corresponding to random variables as a possible solution.
  • #1
venvidu
1
0
Hello all,

Please excuse my naive question that follows.

I do not have much experience in Statistics and need to obtain a set of variables which assures randomness in the variables.

From central limit theorem, I believe addition of random independent variables assures randomness of the overall value ?

In my case, there is a function that takes a set of variables. What I need is to assure randomness in the output of the function. In this case, some of the variables are implicitly dependent on each other. At this point, I am not so clear as to what kind of approach would be proper between just using separate random variables and other approaches with mathematical background, if exist at all ?

Thanks

venvidu
 
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  • #2
I believe you are somewhat confused between variables and values (observed values of the variable). Flip coins, dice or use random number tables to get random values corresponding to some random variable.
 

Related to Question on how to assure randomness for a set of dependent variables

What is the importance of ensuring randomness in a set of dependent variables?

The randomness of a set of dependent variables is crucial for the validity and reliability of scientific experiments and studies. It helps to reduce bias and ensures that the results are representative of the entire population, rather than just a specific group.

How can randomness be assured in a set of dependent variables?

Randomness can be assured through various methods, such as random sampling, random assignment, and randomization techniques. These methods involve randomly selecting participants or assigning them to different groups, which helps to eliminate any potential biases and ensures that each participant has an equal chance of being selected.

What are some common mistakes that can compromise the randomness of a set of dependent variables?

One common mistake is using convenience sampling, where participants are selected based on their easy accessibility. This can lead to a non-representative sample and compromise the randomness of the dependent variables. Another mistake is not properly randomizing the order of tasks or conditions in an experiment, which can introduce biases and affect the results.

Can the randomness of a set of dependent variables be manipulated or controlled?

No, the randomness of a set of dependent variables cannot be controlled or manipulated. It is important to ensure that the randomization process is unbiased and free from any external influences. Any attempt to manipulate or control the randomness can compromise the integrity of the results.

What are some potential consequences of not assuring randomness in a set of dependent variables?

Not ensuring randomness in a set of dependent variables can lead to biased results, which can have a significant impact on the validity and generalizability of the study. It can also raise ethical concerns, as biased results can potentially harm individuals or groups who are affected by the findings of the study.

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