In the inaugural segment of ‘Making Statistical Concepts Accessible,’ we delved into the nuanced world of p-values, providing a clear definition underscored by practical examples. For a detailed understanding, follow the link to the first series:
Making Statistical Concepts Accessible – Edition 1
Our narrative seamlessly connected the concept of p-values to the realm of hypothesis testing. The primary objective of this second series is to demystify hypothesis testing, ensuring a lucid comprehension of this pivotal statistical concept.
Hypothesis testing is a powerful statistical method used to make informed decisions about populations based on sample data. It involves testing a claim or assumption about a population parameter, such as the mean or proportion, using evidence from a sample. The process helps researchers and scientists draw conclusions about the larger population from which the sample was drawn.
Key Steps in Hypothesis Testing (a-e):
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