1

Etapa 1

Part 1 Getting Started

20 junio—30 junio

2

Etapa 2

Part 2 Basic methods

01 julio—15 julio

3

Etapa 3

Part 3

16 julio—19 agosto

4

Etapa 4

Part 4

19 agosto—16 septiembre

1

Etapa 1

Part 1 Getting Started

20 junio—30 junio

2

Etapa 2

Part 2 Basic methods

01 julio—15 julio

3

Etapa 3

Part 3

16 julio—19 agosto

4

Etapa 4

Part 4

19 agosto—16 septiembre

20 junio 2018 31 octubre 2018
Objetivo completado 17 septiembre 2018
General

Пройти книгу по программированию "R in action", Robert I. Kabacoff

If you're little or no R background, it'd be better to read Part I Getting Started and Part II Basic Methods of R in Action.


If you continue Part III Intermediate Methods and Part IV Advanced Methods of that book, the topics are much in common between the two.

However Practical Data Science with R has some distinctive topics, which is data connection, presentation, deployment... Actually the focus is this book is how to complete an analysis project from gathering data to presenting the outcome while the former focuses on how to analysis data. (Note that analysis is only a part of a analysis project.)

In this regards, the following may be options.

Part I and II of R in Action + Practical Data Science with R
Part I to IV of R in Action + Practical Data Science with R

 Criterio del fin

Прочитаны все главы и завершены все примеры из книги

  1. Part 1 Getting Started

    Has 5 chapters

    1. Chapter 1 Introduction to R

    2. Chapter 2 Creating a dataset

    3. Chapter 3 Getting started with graphs

    4. Chapter 4 Basic data management

    5. Chapter 5 Advanced data management

  2. Part 2 Basic methods

    Has 2 chapters

    1. Chapter 6 Basic graphs

    2. Chapter 7 Basic statistics

  3. Part 3

    Has 5 chapters

    1. Chapter 8 Regression

    2. Chapter 9 Analysis of variance

    3. Chapter 10 Power analysis

    4. Chapter 11 Intermediate graphs

    5. Chapter 12 Resampling statistics and bootstraping

  4. Part 4

    Has 4 chapters

    1. Chapter 13 Generalized linear models

    2. Chapter 14 Principal components and factor analysis

    3. Chapter 15 Advanced methods for missing data

    4. Chapter 16 Advanced graphics

  • 410
  • 20 junio 2018, 20:30
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