Following a significant two-way ANOVA, comparisons between glucose concentrations have been evaluated as paired data
(see Table 2 for detailed statistics).
The comparison between paired data
indicated a difference of 99.12+/-200.17 seconds, which was statistically significant (p<0.05).
Statistical analysis using the nonparametric test for paired data
(Wilcoxon matched paired test) obtained a nonsignificant two-tailed P-value of 0.6406.
In most research studies that analyze paired data
, the value of the population correlation [rho] is not known.
n, Number of paired data
points; r, correlation coefficient; CI, confidence interval.
. Second day Second day precipitation-free had precipitation First day precipitation-free 413 pairs 73 pairs First day had precipitation 73 pairs 171 pairs Table 7.
The t test results for paired data
showed high significance (t = 5.42, p < .00001).
on 98 monthly trips of removal of waste from the mountain by Porters (n=49) and cleaning crew (n=49), respectively, were analyzed for the years 2003-2005 combined.
The spreadsheet contains paired data
values (ordered pairs): 2 is paired with 4; 3 is paired with 9, and so on.
Due to the small number of measurements and their non-normal distribution, data were summarised using median (range) and compared using sign rank (paired data
) and Wilcoxon rank sum or Kruskall-Wallis tests (unpaired data).
Second, the percentage of concordance of paired data
in the hypoglycemic, normoglycemic, or hyperglycemic range was calculated.
Correlation coefficients are calculated by comparing each pair of data to other paired data
. For example, if we wanted to check on the possible correlation between yield and phosphorus (P), we would need a data set of yield points from a yield monitor that has an associated P.