I have data on ATPase activity of two types of muscle at different concentrations of Ca 2+ and although the leg muscle seems to be more responsive than the flight i have to prove this statistically
I don't know whether my data is paired or not. I think that it is not paired and thhat i can use a wilcoxon test can you just tell me if i'm right?
Ca 2+ conc ATP activity ATP activity M for leg for flight m muscle muscle
1.00E-09 0.048 0.044
1.00E-08 0.048 0.043
5.00E-08 0.052 0.049
1.00E-07 0.063 0.046
2.50E-07 0.069 0.049
6.50E-07 0.093 0.058
1.00E-06 0.113 0.064
1.00E-05 0.125 0.081
Thanks
Isa
To determine whether your data is paired or not, you need to consider the relationship between the measurements for each condition. In paired data, the observations in one group are matched or related to the observations in the other group. In your case, you have measurements of ATPase activity for both leg muscle and flight muscle at different concentrations of Ca2+.
If the measurements for each concentration of Ca2+ are from the same sample (e.g., the same muscle sample was tested at different concentrations), then your data is considered paired. On the other hand, if the measurements at each concentration of Ca2+ come from different samples (e.g., different individuals or different muscle samples), then your data is considered independent or unpaired.
Based on the information provided, it is not clear whether the data is paired. You need to determine whether the observations for each concentration of Ca2+ are matched or related. If they are matched, then the data is considered paired; otherwise, it is unpaired.
Regarding the statistical test, the Wilcoxon test (also known as the Wilcoxon signed-rank test) is a non-parametric test used for paired data. If your data is indeed paired, you can consider using the Wilcoxon test to compare the ATPase activity between the leg muscle and flight muscle at different concentrations of Ca2+.
However, if your data is unpaired, meaning that the observations at each concentration of Ca2+ come from different samples, you may need to use a different statistical test, such as the Mann-Whitney U test, which is a non-parametric test for independent samples.
To determine the appropriate test, you need to establish whether your data is paired or unpaired based on the information about the relationship between the measurements.