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
·
All our courses can be
Tailor-made to participants needs
·
The participant must be
conversant with English
·
Presentations are
well guided, practical exercises, web-based tutorials, and group work. Our
facilitators are experts with more than 10years of experience
·
Upon completion of
training, the participant will be issued with a Global King Project Management
certificate
·
Training will be done at
the Global King Project Management Centers (Nairobi Kenya, Mombasa Kenya,
Kigali Rwanda, Dubai ,Lagos Nigeria and More others).
·
A discount of 20% will
be given to more than 4 participants from same organization.
·
Course duration is
flexible and the contents can be modified to fit any number of
days.
·
Payment should be done
before commencement of the training, to the Global King Project Management
account, so as to enable us to prepare better for you.
·
For any inquiry
to: [email protected] or +254 114 830 889
·
Website: www.globalkingprojectmanagement.org
·
Tablet and Laptops are
provided to participants on request as an add-on cost to the training fee
·
The course fee for
onsite training includes facilitation training materials, 2 coffee breaks, a
buffet lunch, and a Certificate of successful completion of Training.
Participants will be responsible for their own travel expenses and
arrangements, airport transfers, visa application dinners, health/accident
insurance, and other personal expenses.
Start Date | End Date | Action | Duration | Location | Fee(Kes) | Fee(Us$) |
---|---|---|---|---|---|---|
13/02/2023 | 17/02/2023 | 5Days | Nairobi | 100000 | 1200 | |
10/04/2023 | 14/04/2023 | 5Days | Nairobi | 100000 | 1200 | |
08/05/2023 | 12/05/2023 | 5Days | Nairobi | 100000 | 1200 | |
05/06/2023 | 09/06/2023 | 5Days | Nairobi | 100000 | 1200 | |
03/07/2023 | 07/07/2023 | 5Days | Nairobi | 100000 | 1200 | |
31/07/2023 | 04/08/2023 | 5Days | Nairobi | 100000 | 1200 | |
28/08/2023 | 01/09/2023 | 5Days | Nairobi | 100000 | 1200 | |
23/10/2023 | 27/10/2023 | 5Days | Nairobi | 100000 | 1200 | |
16/01/2023 | 20/01/2023 | 5Days | Mombasa | 120000 | 1500 | |
13/03/2023 | 17/03/2023 | 5Days | Mombasa | 120000 | 1500 | |
25/09/2023 | 29/09/2023 | 5Days | Mombasa | 120000 | 1500 | |
20/11/2023 | 24/11/2023 | 5Days | Mombasa | 120000 | 1500 |