Greater confidence would require more data to generate intervals of usable lengths. When a logarithmic transformation is applied to the data, the distributions are symmetric and the within-treatment variability is about the same. For reporting purposes, this CI should be transformed back to the original scale. A CI for a difference in the log scale becomes a CI for a ratio in the original scale. Take the antilogarithms of the mean difference in the log scale and of the endpoints of the confidence interval.
Confidence intervals contain population values found to be consistent with the data.
If a confidence interval for a mean difference includes 0, the data are consistent with a population mean difference of 0. If the difference is 0, the population means are equal. If the confidence interval for a difference excludes 0, the data are not consistent with equal population means. Therefore, one of the first things to look at is whether a confidence interval for a difference contains 0. If 0 is not in the interval, a difference has been established.