Issue with Understanding Confidence Interval

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: and
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.

Thanks very much if you can assist.


Hi portnoy58, welcome to RStudio Community.

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.

I read the previous posts firsts, and I think this may help you better understand the point
made by siddharthprabhu

Albert Resources – 10 Feb 17

Confidence Intervals: What to Know for Statistics |

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).

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Yes, reading up on confidence intervals is the right approach here to help you understand what those values represent.

Here are a couple of lectures on the subject if video tutorials are more your thing.

Thanks Mr Robin this is a really helpful steer and thanks for the advice on how you interpret this.

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.

An example:
If you draw observations from a distribution repeatedly, your confidence interval will cover the mean in 95% of the time.

The distribution you are sampling from doesn't need to be symmetric.

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