Applied Statistics using R with Data Processing

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Online

£ 20 + VAT

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Description

  • Type

    Course

  • Methodology

    Online

  • Start date

    Different dates available

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 ableYou 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.

Facilities

Location

Start date

Online

Start date

Different dates availableEnrolment now open

About this course

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

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This centre's achievements

2021

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The average rating is higher than 3.7

More than 50 reviews in the last 12 months

This centre has featured on Emagister for 4 years

Subjects

  • Programming
  • Statistics
  • Data Mining

Course programme

R Course 39 lectures 02:02:30 Getting Started 1 Getting Started 2 Getting Started 3 Hello World Application Data Mining Process Download Dataset Read Dataset Mode Median Mean Range Range 2 Range 3 IQR Quantile 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 Duplicates R Course Getting Started 1 Getting Started 1 Getting Started 1 Getting Started 2 Getting Started 2 Getting Started 2 Getting Started 2 Getting Started 3 Getting Started 3 Getting Started 3 Getting Started 3 Hello World Application Hello World Application Hello World Application Hello World Application Data Mining Process Data Mining Process Data Mining Process Data Mining Process Download Dataset Download Dataset Download Dataset Download Dataset Read Dataset Read Dataset Read Dataset Read Dataset Mode Mode Mode Mode Median Median Median Median Mean Mean Mean Mean Range Range Range Range Range 2 Range 2 Range 2 Range 2 Range 3 Range 3 Range 3 Range 3 IQR IQR IQR IQR Quantile Quantile Quantile Quantile Population Variance Population Variance Population Variance Population Variance Sample Variance Sample Variance Sample Variance Sample Variance Variance Variance Variance Variance Standard Deviation Standard Deviation Standard Deviation Standard Deviation Normal Distribution Normal Distribution Normal Distribution Normal Distribution Skewness and Kurtosis Skewness and Kurtosis Skewness and Kurtosis Skewness and Kurtosis Summary and Str Summary and Str Summary and Str Summary and Str Correlation Correlation Correlation Correlation Covariance Covariance Covariance Covariance Inferential Statistics - Tests Inferential Statistics - Tests Inferential Statistics - Tests Inferential Statistics - Tests One Sample T Test One Sample T Test One Sample T Test One Sample T Test Two Sample Unpaired T Test Two Sample Unpaired T Test Two Sample Unpaired T Test Two Sample Unpaired T Test Two Sample Unpaired T Test: Variance Not Equal Two Sample Unpaired T Test: Variance Not Equal Two Sample Unpaired T Test: Variance Not Equal Two Sample Unpaired T Test: Variance Not Equal Two Sample Paired T Test Two Sample Paired T Test Two Sample Paired T Test Two Sample Paired T Test Chi Square Test Chi Square Test Chi Square Test Chi Square Test One Way ANOVA One Way ANOVA One Way ANOVA One Way ANOVA Two Way ANOVA Two Way ANOVA Two Way ANOVA Two Way ANOVA MANOVA MANOVA MANOVA MANOVA Simple Linear Regression Simple Linear Regression Simple Linear Regression Simple Linear Regression Multiple LInear Regression Multiple LInear...

Additional information

Computer Knowledge Basic coding knowledge

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Applied Statistics using R with Data Processing

£ 20 + VAT

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