Meauring deviation of something using some party randomized variables

[clemon!!]

hi,

i want to take an x-y data set and find the deviation from another dataset.

the master dataset is two identical y=1/x curves of different amplitude; also one only registers at periodic intervals and the second is multiplied by a noise signal.


so part of the problem is going to be that the actual master dataset is inexactly defined as the noise signal itself [i used white noise between 1 and 0] is noise - i.e. i need to be able to say when something is just noise - in which case the match is prefect...


make sense? can anyone start me off with this [i still need to find the perfect master dataset actually...]. thanks :) !

 

[Number Nine]

You would probably get better answers if you posted this in the statistics section. You can ask one of the mods to move it for you.

 

[clemon!!]

trying... :)

 

[Stephen Tashi]

hi,

i want to take an x-y data set and find the deviation from another dataset.

You should start by getting your objective clear. "Find the deviation" doesn't define a precise goal. If you want to use statiistical procedures, these fall into two broad categories. There is Hypothesis Testing, which usually considers a yes-or-no type question such as "Are these two data sets measurements of the same underlying phenomenon?" or "Are the mean values of these two distributions identical?". There is Estimation, which considers questions like "What is the mean value of the distribution?" or "What is the numerical difference in the mean values of these two distributions?".

 

[blue_raver22]

I would suggest using statistical methods to measure the deviation between the two datasets. First, you can calculate the mean and standard deviation for each dataset to get an overall understanding of the data. Then, you can use methods such as t-tests or ANOVA to compare the means of the two datasets and determine if there is a significant difference. Additionally, you can use correlation analysis to see if there is a relationship between the two datasets, and if so, how strong it is. It may also be helpful to plot the data and visually compare the two curves to see any patterns or differences. Overall, it's important to carefully select your master dataset and ensure that it accurately represents the data you are trying to measure.