Deep Dive into Statistical Modeling with R [Video]

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Deep Dive into Statistical Modeling with R [Video]

Olgun Aydin

Learn to acquire, manipulate, analyse, and model your data for powerful data analytics with the R programming language.
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Video Details

ISBN 139781788396127
Course Length1 hour and 26 minutes

Video Description

R is a data analysis tool, graphical environment, and programming language. Without any prior experience in programming or statistical software, this video tutorial will help you quickly become a knowledgeable user of R. Now is the time to take control of your data and start producing superior statistical analysis with R.

In this video tutorial, you will start with a quick refresher on programming in R. You will learn to set up your R development environment, as well as work on a few simple R programs. After that you will dive right into working with different types of data structures in R, such as vectors, lists, matrices, etc. You will explore how to import and export data for your data analysis project, and also connect to databases such as PostgreSQL. From there, you will look into probabilities, distributions, and random numbers. Here you will explore discrete distributions, continuous distributions, and random number generation. Finally, you will learn to statistically model your data, and also about hypothesis testing. You will dive into descriptive statistics and graphs, parametric and non-parametric statistical methods, correlation and regression analysis, and time-series analysis.

By the end of this video course, you will be well versed with working with different types of data and modelling your data for your statistical analysis projects with the help of R.

Style and Approach

This video tutorial is a step-by-step, deep dive into all the necessary steps for statistically modelling and analysis of data with the help of the R programming language

Table of Contents

Introduction to R
The Course Overview
What Is R?
Benefits of R
Some Sample R Applications
First Applications in R
Dealing with Problems in Installing R Packages
Data Structures and Working with Data
Vectors and Lists
Matrix and DataFrames
Casting Variables
Data Manipulation
Data Importing and Exporting
Connecting PostgreSQL Databases
Probabilities, Distributions, and Random Numbers
Discrete Distributions
Continuous Distributions
Random Number Generators
Distribution Fitting
Some Tricks about Calculating P-values
Statistical Modelling and Hypothesis Testing
Descriptive Statistics and Graphs
Parametric Statistical Methods
Non-Parametric Statistical Methods
Correlation and Regression Analysis
Time Series Analysis
Missing Value Imputation

What You Will Learn

  • Work with different data structures such as vectors, lists, matrices, and data frames
  • Employ discrete and continuous distributions for analysing your data
  • Model your data with the help of statistical and parametric modelling
  • Decide better models for analysis by studying information criteria
  • Efficiently predict data with the help of correlation and regression analysis

Authors

Table of Contents

Introduction to R
The Course Overview
What Is R?
Benefits of R
Some Sample R Applications
First Applications in R
Dealing with Problems in Installing R Packages
Data Structures and Working with Data
Vectors and Lists
Matrix and DataFrames
Casting Variables
Data Manipulation
Data Importing and Exporting
Connecting PostgreSQL Databases
Probabilities, Distributions, and Random Numbers
Discrete Distributions
Continuous Distributions
Random Number Generators
Distribution Fitting
Some Tricks about Calculating P-values
Statistical Modelling and Hypothesis Testing
Descriptive Statistics and Graphs
Parametric Statistical Methods
Non-Parametric Statistical Methods
Correlation and Regression Analysis
Time Series Analysis
Missing Value Imputation

Video Details

ISBN 139781788396127
Course Length1 hour and 26 minutes
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