Об этом курсе
4.4
79 ratings
20 reviews
Welcome to the Advanced Linear Models for Data Science Class 1: Least Squares. 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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Предполагаемая нагрузка: 6 weeks of study, 1-2 hours/week

Прибл. 10 ч. на завершение
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English

Субтитры: English

Приобретаемые навыки

Linear AlgebraStatisticsR ProgrammingLinear Regression
Globe

Только онлайн-курсы

Начните сейчас и учитесь по собственному графику.
Calendar

Гибкие сроки

Назначьте сроки сдачи в соответствии со своим графиком.
Advanced Level

Продвинутый уровень

Clock

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

Прибл. 10 ч. на завершение
Comment Dots

English

Субтитры: English

Программа курса: что вы изучите

1

Раздел
Clock
1 ч. на завершение

Background

We cover some basic matrix algebra results that we will need throughout the class. This includes some basic vector derivatives. In addition, we cover some some basic uses of matrices to create summary statistics from data. This includes calculating and subtracting means from observations (centering) as well as calculating the variance. ...
Reading
7 видео (всего 28 мин.), 4 материалов для самостоятельного изучения, 1 тест
Video7 видео
Matrix derivatives5мин
Coding example2мин
Centering by matrix multiplication6мин
Coding example2мин
Variance via matrix multiplication6мин
Coding example2мин
Reading4 материала для самостоятельного изучения
Welcome to the class10мин
Course textbook10мин
Grading10мин
In this module10мин
Quiz1 практическое упражнение
Background Quiz12мин

2

Раздел
Clock
1 ч. на завершение

One and two parameter regression

In this module, we cover the basics of regression through the origin and linear regression. Regression through the origin is an interesting case, as one can build up all of multivariate regression with it....
Reading
6 видео (всего 29 мин.), 2 материалов для самостоятельного изучения, 1 тест
Video6 видео
Centering first8мин
Coding example1мин
Connection with linear regression7мин
Coding example1мин
Fitted values and residuals4мин
Reading2 материала для самостоятельного изучения
Before you begin10мин
Before you begin10мин
Quiz1 практическое упражнение
One Parameter Regression Quiz10мин

3

Раздел
Clock
1 ч. на завершение

Linear regression

In this lecture, we focus on linear regression, the most standard technique for investigating unconfounded linear relationships. ...
Reading
8 видео (всего 23 мин.), 2 материалов для самостоятельного изучения, 1 тест
Video8 видео
Coding example1мин
Prediction2мин
Coding example2мин
Residuals2мин
Coding example1мин
Generalizations6мин
Generalizations example2мин
Reading2 материала для самостоятельного изучения
Before you begin10мин
Generalizations10мин
Quiz1 практическое упражнение
Linear Regression Quiz12мин

4

Раздел
Clock
1 ч. на завершение

General least squares

We now move on to general least squares where an arbitrary full rank design matrix is fit to a vector outcome....
Reading
6 видео (всего 39 мин.), 1 материал для самостоятельного изучения, 1 тест
Video6 видео
Coding example3мин
Second derivation of least squares4мин
Projections9мин
Third derivation of least squares12мин
Coding example4мин
Reading1 материал для самостоятельного изучения
Before you begin10мин
Quiz1 практическое упражнение
General Least Squares Quiz20мин
4.4

Лучшие рецензии

автор: DLJun 8th 2016

We need more advanced, theoretical courses on Coursera, like this one, in order to deeply understand the more general courses like Regression Models and Linear Models.

автор: SPApr 30th 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.

Преподаватель

Brian Caffo, PhD

Professor, Biostatistics
Bloomberg School of Public Health

О 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....

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  • 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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