QUANTITATIVE DATA MANAGEMENT AND ANALYSIS WITH R COURSE

QUANTITATIVE DATA MANAGEMENT AND ANALYSIS WITH R COURSE

Start Date: 11/10/2021 End Date: 15/10/2021 for 5 days
Register online: https://bit.ly/2HuPEVv

Organizer: DATA-AFRIQUE CONSULTANCY (www.data-afriqueconsultancy.org)
Course fee: USD 1,000

Introduction

This course is designed for participants who plan to use R for the management, coding, analysis and visualization of qualitative data. The course’s content is spread over seven modules and includes: Basics of Applied Statistical Modelling, Essentials of the R Programming, Statistical Tools, Probability Distributions, Statistical Inference, Relationship between Two Different Quantitative Variables and Multivariate Analysis . The course is entirely hands-on and uses sample data to learn R basics and advanced features.

Duration

5 days

Who Should Attend?

Statistician, analyst, or a budding data scientist and beginners who want to learn how to analyze data with R,

Course Objective:

· Analyze t data by applying appropriate statistical techniques

· Interpret the statistical analysis

· Identify statistical techniques a best suited to data and questions

· Strong foundation in fundamental statistical concepts

· Implement different statistical analysis in R and interpret the results

· Build intuitive data visualizations

· Carry out formalized hypothesis testing

· Implement linear modelling techniques such multiple regressions and GLMs

· Implement advanced regression analysis and multivariate analysis

Course content

MODULE ONE: Basics of Applied Statistical Modelling

· Introduction to the Instructor and Course

· Data & Code Used in the Course

· Statistics in the Real World

· Designing Studies & Collecting Good Quality Data

· Different Types of Data

MODULE TWO: Essentials of the R Programming

· Rationale for this section

· Introduction to the R Statistical Software & R Studio

· Different Data Structures in R

· Reading in Data from Different Sources

· Indexing and Subletting of Data

· Data Cleaning: Removing Missing Values

· Exploratory Data Analysis in R

MODULE THREE: Statistical Tools

· Quantitative Data

· Measures of Center

· Measures of Variation

· Charting & Graphing Continuous Data

· Charting & Graphing Discrete Data

· Deriving Insights from Qualitative/Nominal Data

MODULE FOUR: Probability Distributions

· Data Distribution: Normal Distribution

· Checking For Normal Distribution

· Standard Normal Distribution and Z-scores

· Confidence Interval-Theory

· Confidence Interval-Computation in R

MODULE FIVE: Statistical Inference

· Hypothesis Testing

· T-tests: Application in R

· Non-Parametric Alternatives to T-Tests

· One-way ANOVA

· Non-parametric version of One-way ANOVA

· Two-way ANOVA

· Power Test for Detecting Effect

MODULE SIX: Relationship between Two Different Quantitative Variables

· Explore the Relationship Between Two Quantitative Variables

· Correlation

· Linear Regression-Theory

· Linear Regression-Implementation in R

· Conditions of Linear Regression

· Multi-collinearity

· Linear Regression and ANOVA

· Linear Regression With Categorical Variables and Interaction Terms

· Analysis of Covariance (ANCOVA)

· Selecting the Most Suitable Regression Model

· Violation of Linear Regression Conditions: Transform Variables

· Other Regression Techniques When Conditions of OLS Are Not Met

· Regression: Standardized Major Axis (SMA) Regression

· Polynomial and Non-linear regression

· Linear Mixed Effect Models

· Generalized Regression Model (GLM)

· Logistic Regression in R

· Poisson Regression in R

· Goodness of fit testing

MODULE SEVEN: Multivariate Analysis

· Introduction Multivariate Analysis

· Cluster Analysis/Unsupervised Learning

· Principal Component Analysis (PCA)

· Linear Discriminant Analysis (LDA)

· Correspondence Analysis

· Similarity & Dissimilarity Across Sites

· Non-metric multi-dimensional scaling (NMDS)

· Multivariate Analysis of Variance (MANOVA)

General Notes

• This course is delivered by our seasoned trainers who have vast experience as expert professionals in the respective fields of practice. The course is taught through a mix of practical activities, theory, group works and case studies.
• Training manuals and additional reference materials are provided to the participants.
• Upon successful completion of this course, participants will be issued with a certificate.
• We can also do this as tailor-made course to meet organization-wide needs. Contact us to find out more: [email protected]
• The training will be conducted at DATA-AFRIQUE TRAINING CENTRE, Nairobi Kenya.
• The training fee covers tuition fees, training materials, lunch and training venue. Accommodation and airport transfer are arranged for our participants upon request.
• Payment should be sent to our bank account before start of training and proof of payment sent to: [email protected]