BS 12: Quick summary of Linear Regression sub series

Continuing with biostatistics series of IAPSM econnect, which is a series of short videos each targeting a specific concept of biostatistics which are commonly encountered and often confusing but are vital for understanding a research paper or designing a research study or doing analysis.
In this last video of Linear regression sub series, chapter 8, we provide a quick summary of what has been discussed in previous videos of this sub series. Due to some technical issues chapter 7 of this sub series could not be uploaded currently. Here, we start by discussing the importance of data cleaning and preparing your dataset for analysis. Next, we dive into assumption validation, highlighting key assumptions like linearity, normality, homoscedasticity, and independence. We explore alternatives for cases where assumptions aren’t met. Finally, we wrap it all up with a take-home message.
Don't forget to check out the full series for in-depth explanations and examples!
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