How to Compare Two Groups of Signals?

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Rightia Rollmann
Rightia Rollmann 2017 年 3 月 27 日
コメント済み: the cyclist 2017 年 3 月 27 日
Imagine I have two groups of signals A and B having four and three samples, respectively.
A1 = [1 3 -1 2];
A2 = [1 3 -2 3];
A3 = [1 4 -3 4];
A4 = [2 4 -2 3];
B1 = [2 3 -1 5];
B2 = [2 4 -2 6];
B3 = [2 4 -4 5];
How can I find out whether there is a statistically significant difference between groups A and B?

回答 (2 件)

the cyclist
the cyclist 2017 年 3 月 27 日
編集済み: the cyclist 2017 年 3 月 27 日
To determine whether these signals are significantly different, you first need to define a null hypothesis that will define the range of typical differences. This generally involves an underlying theoretical model, such as "these samples are all drawn from the a normal distribution with the same parameters".
What is your null hypothesis? If your answer is, "I don't have one", then you cannot do hypothesis testing, or determine statistically significant differences.
  4 件のコメント
the cyclist
the cyclist 2017 年 3 月 27 日
And what do the four numbers in A1 represent? Four different amplitudes, at four different time points? Why are they always integers, rather than values like 1.63?

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John BG
John BG 2017 年 3 月 27 日
When comparing signals this way you could start averaging both signals amplitude this way:
A=[A1;A2;A3;A4];B=[B1;B2;B3];
mean(A)
=
1.25 3.50 -2.00 3.00
mean(B)
=
2.00 3.67 -2.33 5.33
then could check time average
mean(mean(A))
=
1.44
mean(mean(B))
=
2.17
that was 1st order statistical all-weather very useful mean, now 2nd order, variance:
var(mean(A))
ans =
6.18
var(mean(B))
ans =
10.85
the more samples the better, the longer the signals the more accurate the measurements
You may also want to see if the signals match a known statistical probability distributions that you may think would fit, for instance normal
fitdist(A,'Normal')
this in turn will give the probability distrition, then you can generate the pdf curve and measure how far the points of the signals are from the probability. The distance of the samples to an expected curve is an error measurement you may find useful
Error Vector Measurements are common in for instance DVB-T or for the case, any IQ signals.
if you find these lines useful would you please mark my answer as Accepted Answer?
To any other reader, if you find this answer of any help, would you please click on the thumbs-up vote link,
thanks in advance for time and attention
John BG

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