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Here, I will try my best to break down statistical concepts into various ways that can be easily understood, at the same time serve as summary notes during my journey of learning by Alvin Mak, Nanyang Technological University published in Towards Data Science.
Population V.S The Sample
Many a times we conduct surveys on a small sample size simply because it is unfeasible to survey an entire population. This sample then allows us to draw inferences about the actual population. The study of statistics largely answers this question: To what confidence can I trust that the sample results speak the truth about the population?
This method of making generalizations about a population is called inferential statistics. Before we get to that, let us recap some basic descriptive statistics we would have come across in our earlier schooling days...
The concept of confidence intervals and significance levels is used extensively in statistics and machine learning techniques. While it does provide a range of estimates for the population parameter at a relatively high confidence, there exists a chance of error where the mean actually lies outside of the stated confidence interval. More will be covered in my next post on Hypothesis Testing. Stay tuned!
Source: Medium
