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Lecture sheet: docs.google.com/document/d/1XoCpny_G-0tEuybW_60osmTFu4R0PVx1pw5HxIyNmZk/edit?usp=sharing

In this chapter, we will study a little bit more of descriptive statistics: Skewness and Group Data. Lecture sheet: docs.google.com/document/d/1XoCpny_G-0tEuybW_60osmTFu4R0PVx1pw5HxIyNmZk/edit?usp=sharing

I made a slight mistake in the calculation of quantiles in the last video (Lecture 2). Not a mistake at all, you still get a reasonable value, but this is not how academically you should calculate quantiles. So, I am describing the formal rule here. The lecture sheet is also updated : docs.google.com/document/d/1XoCpny_G-0tEuybW_60osmTFu4R0PVx1pw5HxIyNmZk/edit?usp=sharing

Lecture sheet: docs.google.com/document/d/1XoCpny_G-0tEuybW_60osmTFu4R0PVx1pw5HxIyNmZk/edit?usp=sharing

Hi, in this video, I discussed the prerequisites that is necessary to understand the upcoming concepts in biostatistics. However, please watch the video carefully till the "Parameter and Statistics" portion. That part and parts before it is important for the exams. Lecture sheet: docs.google.com/document/d/1XoCpny_G-0tEuybW_60osmTFu4R0PVx1pw5HxIyNmZk/edit?usp=sharing Also sorry because I forgot...

Slides: www.academia.edu/126566358/Deep_Neural_Network Colab file (classification): colab.research.google.com/drive/1h-VgKBgvz8XlE4mNASPt0jtoPgPUlQMF?usp=sharing Colab file (regression) : colab.research.google.com/drive/1fr0ySlNVPseMLFLOAXwqyxlBMRFSZ5-O?usp=sharing

Parts that I skipped in the video is covered in this colab notebook: shorturl.at/sSFHf