Bases, introduction

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Destrezas que aprenderás

Statistics, Linear Regression, R Programming, Linear Algebra

Reseñas

4.4 (171 calificaciones)

  • 5 stars
    60,23 %
  • 4 stars
    26,90 %
  • 3 stars
    8,18 %
  • 2 stars
    3,50 %
  • 1 star
    1,16 %

SP

29 de abr. de 2017

Good mathematical rigour for the analysis of linear models. Builds some good intuition for the geometry of least squares which helps in model result interpretation.

HM

11 de jun. de 2016

As the name says it's an advanced course. Take the challenge though! In my opinion the content is a must if you want to perform competently in data science.

De la lección

Bases and residuals

Here we give a very useful kind of linear model, that is decomposing a signal into a basis expansion.

Impartido por:

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    Brian Caffo, PhD

    Professor, Biostatistics

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