What is sample mean?
In this post, we understand that a sample mean, \bar{x} , is an estimate of the associated population mean \mu , and that the sample standard deviation, s , is an estimate of the associated population standard deviation, \sigma , and that these estimates get better as the sample size increases and when we have independent observations. The sample mean is the average of all the measurements in the sample, and if the sample is random, then the sample mean can be used to estimate the population mean.
This post is a part of the Prelim Maths Advanced course under the topic Statistical Analysis and sub-part Discrete Probability Distributions, specifically focusing on sample mean.
Further explanation and examples
The following two videos give us an insight into what the sampling distribution of the sample mean means, and how a normal distribution curve can be graphed.
Part 1: Sampling distribution of the sample mean
