Confidence Interval calculation for a list of means in a dataset

Hi,

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

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.

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