Hello. I need a little hand holding and direction. Just carried out a t.test and ]got the following result in console:slight_smile:

Welch Two Sample t-test

data: Treatment.group and Control.group
t = 2.4139, df = 27.89, p-value = 0.0226
alternative hypothesis: true difference in means is not equal to 0
95 percent confidence interval:
0.05626425 0.68773575
sample estimates:
mean of x mean of y
3.211333 2.839333

I am happy with the p-value and understand what it is saying. I am now looking to report the 95% confidence interval for this test. This is where I need help. Can I calculate this from this result or do I need to run another test? The data of interest is the weight of new born babies in kilogrammes.

t.test() reports the 95% confidence interval for the mean. From your output, the lower confidence bound is 0.05626425 while the upper confidence bound is 0.68773575.

Thanks for your help Mr Siddharth, very much appreciated. I am new to both R and statistics so please bear with me! It's really helpful for you to clarify that these are lower and upper bounds. I am not really sure how to interpret this! er.... is this saying that there is between a 0.06 and 0.69 probability of the test achieving the same outcome if we were to run the same trial again or what?! Once more your help much appreciated.

This article reviews confidence intervals, including how to interpret them and differences between one-sided and two-sided confidence intervals.

In short it suggests the true mean of the data set lies somewhere in the 0.06 and 0.69 range. It suggests we are 95% sure that the true mean is somewhere in that range, but doesn't suggest that 95% of the data set falls within that range (a common mistake).

Once more Mr Siddharth thanks for your kindness. These are great links ...just what I need. I think I have got my head round this matter now. Thanks again for your help and support.