Hey, I’ve been going through the data scientist path and currently working on the central limit theorem.
Here’s the link to the page

There is a line which isn’t making sense to me when I go through the heading ‘How does this help the data scientist?’.

Once we calculate the standard error as part of the CLT, why do we have to multiply it with 1.275? Then, the next line multiplies 1.275 with 1.96. It is interesting to mention here that 1.275 is the standard error given. Refer the screenshot below:

First, the data scientist needs to multiply 1.275 by the estimated standard error:

I think 1.275 here is a typo for 1.96.

1.96 (see this Wikipedia page) is the 97.5 percentile point of the standard normal distribution (it is, normal distribution with mean 0 and standard deviation 1). If a random variable follows the standard normal distribution, there is about 95% probability of taking a value between -1.96 and 1.96.

Our data scientist has calculated a standard error of 1.275. It means that the estimated sampling distribution is the normal distribution with the standard deviation of 1.275. It will have the shape that is stretched the standard normal distribution 1.275 times horizontally. So there is about 95% probability that a sample mean will be in the range plus-minus 1.275 * 1.96 of the population mean.

I thought that this was a typo but to be sure, I wanted to run it by someone first.
Awesome! I get it now. The wikipedia page clears out a lot of confusion. Thanks for helping out, @object2161442840!