INTRODUCTION
New
developments in data science offer a tremendous opportunity to improve
decision-making. In the development world, there has been an increase in
the number of data gathering initiative such as baseline surveys,
Socio-Economic Surveys, Demographic and Health Surveys, Nutrition Surveys, Food
Security Surveys, Program Evaluation Surveys, Employees, customers and vendor
satisfaction surveys, and opinion polls among others, all intended to provide
data for decision making.
It
is essential that these efforts go beyond merely generating new insights from
data but also to systematically enhance individual human judgment in real
development contexts. How can organizations better manage the process of
converting the potential of data science to real development outcomes. This ten
days hands-on course is tailored to put all these important consideration into
perspective. It is envisioned that upon completion, the participants will be
empowered with the necessary skills to produce accurate and cost effective data
and reports that are useful and friendly for decision making.
It
will be conducted using ODK, GIS, NVIVO and R.
COURSE
OBJECTIVES
At the end of course participants should be able to:
·
Understand and appropriately
use statistical terms and concepts
·
Design and Implement
universally acceptable Surveys
·
Convert data into various formats
using appropriate software
·
Use mobile data gathering tools such
as Open Data Kit (ODK)
·
Use GIS software to plot and display
data on basic maps
·
Qualitative data analysis using
NVIVO
·
Analyze t data by applying
appropriate statistical techniques using R
·
Interpret the statistical analysis
using R
·
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
·
Write reports from survey data
·
Put strategies to improve data
demand and use in decision making
DURATION
10 Days
WHO
SHOULD ATTEND
This is a general
course targeting participants with elementary knowledge of Statistics from
Agriculture, Economics, Food Security and Livelihoods, Nutrition, Education,
Medical or public health professionals among others who already have some
statistical knowledge, but wish to be conversant with the concepts and
applications of statistical modeling.
COURSE
CONTENT
Module1: Basic
statistical terms and concepts
·
Introduction to statistical concepts
·
Descriptive Statistics
·
Inferential statistics
Module
2: Research Design
·
The role and purpose of research
design
·
Types of research designs
·
The research process
·
Which method to choose?
·
Exercise: Identify a project of
choice and developing a research design
Module
3: Survey Planning, Implementation and Completion
·
Types of surveys
·
The survey process
·
Survey design
·
Methods of survey sampling
·
Determining the Sample size
·
Planning a survey
·
Conducting the survey
·
After the survey
·
Exercise: Planning for a survey
based on the research design selected
Module
4: Introduction
·
Introduction to Mobile Data
gathering
·
Benefits of Mobile Applications
·
Data and types of Data
·
Introduction to common mobile
based data collection platforms
·
Managing devices
·
Challenges of Data Collection
·
Data aggregation, storage and
dissemination
·
Types of questions
·
Data types for each question
·
Types of questionnaire or Form logic
·
Extended data types geoid, image and
multimedia
Module
5: Survey Authoring
·
Design forms using a web interface
using:
·
ODK Build
·
Koboforms
·
PurcForms
·
Hands-on Exercise
Module
6: Preparing the mobile phone for data collection
·
Installing applications: ODK Collect
·
Using Google play
·
Manual install (.apk files)
·
Configuring the device (Mobile
Phones)
·
Uploading the form into the mobile
devices
·
Hands-on Exercise
Module
7: Designing forms manually: Using XLS Forms
·
Introduction to XLS forms syntax
·
New data types
·
Notes and dates
·
Multiple choice Questions
·
Multiple Language Support
·
Hints and Metadata
·
Hands-on Exercise
Module
8: Advanced survey Authoring
·
Conditional Survey Branching
·
Required questions
·
Constraining responses
·
Skip: Asking Relevant questions
·
The specify other
·
Grouping questions
·
Skipping many questions at once
(Skipping a section)
·
Repeating a set of questions
·
Special formatting
·
Making dynamic calculations
Module
9: Hosting survey data (Online)
·
ODK Aggregate
·
Formhub
·
io
·
KoboToolbox
·
Uploading forms to the server
Module
10: Hosting Survey Data (Configuring a local server)
·
Configuring ODK Aggregate on a local
server
·
Downloading data
·
Manual download (ODK Briefcase)
·
Using the online server interface
Module
11: GIS mapping of survey data using QGIS
·
Introduction to GIS for Researchers
and data scientists
·
Importing survey data into a GIS
·
Mapping of survey data using QGIS
·
Exercise: QGIS mapping exercise.
Module
12: Understanding Qualitative Research
·
Qualitative Data
·
Types of Qualitative Data
·
Sources of Qualitative data
·
Qualitative vs Quantitative
·
NVivo key terms
·
The NVivo Workspace
Module
13: Preliminaries of Qualitative data Analysis
·
What is qualitative data analysis
·
Approaches in Qualitative data
analysis; deductive and inductive approach
·
Points of focus in analysis of text
data
·
Principles of Qualitative data
analysis
·
Process of Qualitative data analysis
Module
14: Introduction to NVIVO
·
NVIVO Key terms
·
NVIVO interface
·
NVIVO workspace
·
Use of NVIVO ribbons
Module
15: NVIVO Projects
·
Creating new projects
·
Creating a new project
·
Opening and Saving project
·
Working with Qualitative data files
·
Importing Documents
·
Merging and exporting projects
·
Managing projects
·
Working with different data sources
Module
16: Nodes in NVIVO
·
Theme codes
·
Case nodes
·
Relationships nodes
·
Node matrices
·
Type of Nodes,
·
Creating nodes
·
Browsing Nodes
·
Creating Memos
·
Memos, annotations and links
·
Creating a linked memo
Module
17: Classes and summaries
·
Source classifications
·
Case classifications
·
Node classifications
·
Creating Attributes within NVivo
·
Importing Attributes from a
Spreadsheet
·
Getting Results; Coding Query and
Matrix Query
Module
18: Coding
·
Data-driven vs theory-driven coding
·
Analytic coding
·
Descriptive coding
·
Thematic coding
·
Tree coding
Module
19: Thematic Analytics in NVIVO
·
Organize, store and retrieve data
·
Cluster sources based on the words
they contain
·
Text searches and word counts
through word frequency queries.
·
Examine themes and structure in your
content
Module
20: Queries using NVIVO
·
Queries for textual analysis
·
Queries for exploring coding
Module
21: Building on the Analysis
·
Content Analysis; Descriptive,
interpretative
·
Narrative Analysis
·
Discourse Analysis
·
Grounded Theory
Module
22: Qualitative Analysis Results Interpretation
·
Comparing analysis results with
research questions
·
Summarizing finding under major
categories
·
Drawing conclusions and lessons
learned
Module
23: Visualizing NVIVO project
·
Display data in charts
·
Creating models and graphs to
visualize connections
·
Tree maps and cluster analysis
diagrams
·
Display your data in charts
·
Create models and graphs to
visualize connections
·
Create reports and extracts
Module
24: Triangulating results and Sources
·
Triangulating with quantitative data
·
Using different participatory
techniques to measure the same indicator
·
Comparing analysis from different
data sources
·
Checking the consistency on
respondent on similar topic
Module
25: Report Writing
·
Qualitative report format
·
Reporting qualitative research
·
Reporting content
·
Interpretation
MODULE
26: Basics of Applied Statistical Modelling using R
·
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
27: 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
28: 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
29: 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
30: 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
31: 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
32: 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)
Module
33: Report writing for surveys, data dissemination, demand and use
·
Writing a report from survey data
·
Communication and dissemination
strategy
·
Context of Decision Making
·
Improving data use in decision
making
·
Culture Change and Change Management
·
Preparing a report for the survey, a
communication and dissemination plan and a demand and use strategy.
·
Presentations and joint action
planning
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: training@skillsforafrica.org
· The training will be conducted at SKILLS FOR AFRICA TRAINING INSTITUTE IN 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: training@skillsforafrica.org
Dates | Fees | Location | Apply |
---|---|---|---|
06/11/2023 - 17/11/2023 | $3000 | Mombasa | Physical Class Online Class |
04/12/2023 - 15/12/2023 | $2700 | Nairobi | Physical Class Online Class |
15/01/2024 - 26/01/2024 | $3000 | Nairobi | Physical Class Online Class |
12/02/2024 - 23/02/2024 | $3000 | Mombasa | Physical Class Online Class |
11/03/2024 - 22/03/2024 | $3000 | Nairobi | Physical Class Online Class |
08/04/2024 - 19/04/2024 | $3950 | Kigali | Physical Class Online Class |
13/05/2024 - 24/05/2024 | $5500 | Dubai | Physical Class Online Class |
10/06/2024 - 21/06/2024 | $3000 | Nairobi | Physical Class Online Class |
08/07/2024 - 19/07/2024 | $3000 | Nairobi | Physical Class Online Class |
12/08/2024 - 19/07/2024 | $3000 | Nairobi | Physical Class Online Class |
09/09/2024 - 20/09/2024 | $3000 | Nairobi | Physical Class Online Class |
14/10/2024 - 25/10/2024 | $3950 | Kigali | Physical Class Online Class |
11/11/2024 - 22/11/2024 | $3000 | Mombasa | Physical Class Online Class |
09/12/2024 - 20/12/2024 | $3000 | Nairobi | Physical Class Online Class |