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Quantitative Data Management and Analysis with R Course

By: Foscore Development Center

Kenya

20 - 24 Jun, 2022  5 days

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USD 1,000

Venue: Foscore Development Center, Nairobi, Kenya

Other Dates

Venue Date Fee  
Foscore Development Center, Nairobi, Kenya, Kenya 12 - 16 Sep, 2022 USD1000
Foscore Development Center, Nairobi, Kenya, Kenya 05 - 09 Dec, 2022 USD1000

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.

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 and Code Used in the Course
  • Statistics in the Real World
  • Designing Studies and 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 and 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 and Graphing Continuous Data
  • Charting and 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 and Dissimilarity Across Sites
  • Non-metric multi-dimensional scaling (NMDS)
  • Multivariate Analysis of Variance (MANOVA)

Note

  • All our courses can be Tailor-made to participants needs
  • Course duration is flexible and the contents can be modified to fit any number of days.
  • Presentations are well guided, practical exercise, web based tutorials and group work. Our facilitators are expert with more than 10years of experience.
  • One year free Consultation and Coaching provided after the course.
Foscore Development Center, Nairobi, Kenya Jun 20 - 24 Jun, 2022
Foscore Development Center, Nairobi, Kenya, Kenya 12 - 16 Sep, 2022
Foscore Development Center, Nairobi, Kenya, Kenya 05 - 09 Dec, 2022
USD 1,000.00
(Convert Currency)

Jackson Munene +254 712260031

A discount of 20% for 5 or more participants
Foscore Development Center

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