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Applied Statistics using R with Data Processing

Applied Statistics using R with Data Processing

This is the bite size course to learn R Programming for Applied Statistics. In CRISP DM data mining process, Applied Statistics is at the Data Understanding stage. This course also covers Data processing, which is at the Data Preparation Stage.

Overview

About this Course
This is the bite size course to learn R Programming for Applied Statistics. In CRISP DM data mining process, Applied Statistics is at the Data Understanding stage. This course also covers Data processing, which is at the Data Preparation Stage.

You will need to know some R programming, and you can learn R programming from my "Create Your Calculator: Learn R Programming Basics Fast" course. You will learn R Programming for applied statistics and you will be able

You can take the course as follows, I may allow you to have the SVBook certificate in Data Mining using R in future after you passed a quiz and completed all the courses below:

Create Your Calculator: Learn R Programming Basics Fast (R Basics)
Applied Statistics using R with Data Processing (Data Understanding and Data Preparation)
Advanced Data Visualizations using R with Data Processing (Data Understanding and Data Preparation, in future)
Machine Learning with R (Modeling and Evaluation)
I will create advanced data visualizations using R for data understanding stage and includes some data processing for data preparation stage in future.

References:

This course is actually based on the Learn R for Applied Statistics book I have published at Apress.

Basic knowledge
Computer Knowledge
Basic coding knowledge

Course Information

Computer Knowledge
Basic coding knowledge

Content

Getting Started
Getting Started 2
Getting Started 3
Data Mining Process
Download Data set
Read Data set
Mode
Median
Mean
Range
Range 2
Range 3
IQR
Qunatile
Population Variance
Sample Variance
Variance
Standard Deviation
Normal Distribution
Skewness and Kurtosis
Summary() and Str()
Correlation
Covariance
Inferential Statistics Tests
One Sample T Test
Two Sample Unpaired T Test
Two Sample Unpaired T Test (Variance not Equal)
Two Sample Paired T Test
Chi Square Test
One Way ANOVA
Two Way ANOVA
MANOVA
Simple Linear Regression
Multiple LInear Regression
Data Processing: Select Variables
Data Processing: Sort Data
Data Processing: Filter Data
Data Processing: Remove Missing Values and Remove Duplicates

Beginner Data Scientist or Analyst interested in R programming

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Course Specifications

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A short course is a learning programme that gives you combined content or specific skills training in a short period of time. Short courses often lean towards the more practical side of things and have less theory than a university course – this gives you a more hands-on experience within your field of interest.

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Course duration is 24 hours.

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