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What statistical test should be used to compare two groups of frequencies or proportions?
Chi-square test of independence
For more than two groups, test for several proportions can be used. Ultimately, it is the Chi-square test of independence between the two attributes.
How do you calculate upper and lower sideband frequencies?
For example, if C:M is 1:2, that is, the modulator is twice the frequency of the carrier, then the first upper sideband is: C+M = 1+2 = 3. The second upper sideband is: C+2M = 1+(2×2) = 1+4 = 5. Another way to get the second sideband is to add M=2 to the value of the first sideband which is 3; i.e. (C+M) + M = 3+2 = 5.
How to compare frequency of observations between two groups?
I am looking for statistical methods used to compare frequency of observations between two groups. I have two geographical locations with data on different soil types present. Each location has soil types A, B, C, D. The numbers are the number of times a specific soil type occurs in that location.
What should the frequency of Group A be?
If Group A has three students, and each produced 10 hedgings in their essays, frequency will be 30 (3 students x 10 hedging). But how about non-hedging events? if the frequency is based on the appearance of particular phenomena and there is no absolute value, I’m not sure what the frequency looks like.
How to statistically compare two time series?
This common model could be estimated globally and separately for each of the two series and then one could construct an F test to test the hypothesis of a common set of parameters. Consider the grangertest () in the lmtest library. It is a test to see if one time series is useful in forecasting another. Just came across this.
Which is statistical method for comparing frequency counts?
For this you have the counts of each incident for (First/Early/Lifetime), and the null proportions for each category. That is, you use (0.3333, 0.3333, 0.3333) for the “expected” proportions. So a significant test suggests the counts do not follow these “expected” proportions.