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4.7
24 ratings
2 reviews
Welcome to the Advanced Linear Models for Data Science Class 2: Statistical Linear Models. This class is an introduction to least squares from a linear algebraic and mathematical perspective. Before beginning the class make sure that you have the following: - A basic understanding of linear algebra and multivariate calculus. - A basic understanding of statistics and regression models. - At least a little familiarity with proof based mathematics. - Basic knowledge of the R programming language. After taking this course, students will have a firm foundation in a linear algebraic treatment of regression modeling. This will greatly augment applied data scientists' general understanding of regression models....
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Advanced Level

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Sugerido: 6 weeks of study, 1-2 hours/week

Aprox. 9 horas para completar
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Subtítulos: English
Globe

Cursos 100 % en línea

Comienza de inmediato y aprende a tu propio ritmo.
Calendar

Fechas límite flexibles

Restablece las fechas límite en función de tus horarios.
Advanced Level

Nivel avanzado

Clock

Sugerido: 6 weeks of study, 1-2 hours/week

Aprox. 9 horas para completar
Comment Dots

English

Subtítulos: English

Programa - Qué aprenderás en este curso

1

Sección
Clock
2 horas para completar

Introduction and expected values

In this module, we cover the basics of the course as well as the prerequisites. We then cover the basics of expected values for multivariate vectors. We conclude with the moment properties of the ordinary least squares estimates. ...
Reading
7 videos (Total: 38 min), 3 readings, 1 quiz
Video7 videos
Multivariate expected values, the basics4m
Expected values, matrix operations2m
Multivariate variances and covariances5m
Multivariate covariance and variance matrix operations5m
Expected values of quadratic forms3m
Expected value properties of least squares estimates13m
Reading3 lecturas
Welcome to the class10m
Course textbook10m
Introduction to expected values10m
Quiz1 ejercicio de práctica
Expected Values30m

2

Sección
Clock
1 hora para completar

The multivariate normal distribution

In this module, we build up the multivariate and singular normal distribution by starting with iid normals....
Reading
4 videos (Total: 31 min), 2 readings, 1 quiz
Video4 videos
The singular normal distribution7m
Normal likelihoods5m
Normal conditional distributions8m
Reading2 lecturas
Introduction to the multivariate normal10m
A note on the last quiz question.10m
Quiz1 ejercicio de práctica
the multivariate normal20m

3

Sección
Clock
1 hora para completar

Distributional results

In this module, we build the basic distributional results that we see in multivariable regression....
Reading
8 videos (Total: 60 min), 1 reading, 1 quiz
Video8 videos
Confidence intervals for regression coefficients6m
F distribution4m
Coding example7m
Prediction intervals11m
Coding example5m
Confidence ellipsoids7m
Coding example6m
Reading1 lectura
Distributional results10m
Quiz1 ejercicio de práctica
Distributional results20m

4

Sección
Clock
1 hora para completar

Residuals

In this module we will revisit residuals and consider their distributional results. We also consider the so-called PRESS residuals and show how they can be calculated without re-fitting the model....
Reading
4 videos (Total: 32 min), 2 readings, 1 quiz
Video4 videos
Code demonstration3m
Leave one out residuals8m
Press residuals14m
Reading2 lecturas
Residuals10m
Thanks for taking the course10m
Quiz1 ejercicio de práctica
Residuals14m
4.7

Principales revisiones

por MLJan 31st 2017

Good course on applied linear statistical modeling.

Instructor

Brian Caffo, PhD

Professor, Biostatistics
Bloomberg School of Public Health

Acerca de Johns Hopkins University

The mission of The Johns Hopkins University is to educate its students and cultivate their capacity for life-long learning, to foster independent and original research, and to bring the benefits of discovery to the world....

Preguntas Frecuentes

  • Once you enroll for a Certificate, you’ll have access to all videos, quizzes, and programming assignments (if applicable). Peer review assignments can only be submitted and reviewed once your session has begun. If you choose to explore the course without purchasing, you may not be able to access certain assignments.

  • When you purchase a Certificate you get access to all course materials, including graded assignments. Upon completing the course, your electronic Certificate will be added to your Accomplishments page - from there, you can print your Certificate or add it to your LinkedIn profile. If you only want to read and view the course content, you can audit the course for free.

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