Confidence Interval calculation for a list of means in a dataset


I am wondering if someone can help me out, I need to calculate Confidence Intervals for a column in my dataset. The column (avg_in1000) has values of the average value which can be equated as the mean. Is there a way to calculate the CI in R?

Also, for the dataset, I have calculated the linear and segmented model. Mentioning this just in case the CI can be calculated using one of these.

A picture of a sample is dataframe is attached.

t.test(data$avg_in) will report a t-test for a single mean along with a confidence interval, defaults to 95% confidence. The result can always be stored as object to isolate just the confidence interval from result$

Hey, thanks for getting back to my query. This works but I just get one set of values which I am assuming is for the column labelled " avg_in", rather than for each row of the column "avg_in". Any way to make this work?

Given that the t-formula requires a sample standard deviation and the standard deviation is undefined for a single value, no.

This topic was automatically closed 21 days after the last reply. New replies are no longer allowed.

If you have a query related to it or one of the replies, start a new topic and refer back with a link.