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Research Design,SurveyCTO Mobile data collection,GIS Mapping,Data analysis using NVIVO and R course

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Upcoming Training Schedules 14 locations
Location Duration Next Start Date Dates Available Action
Nairobi, Kenya 10 days Jul 13, 2026 104 dates
Accra, Ghana 10 days Jul 27, 2026 31 dates
Addis Ababa, Ethiopia 10 days Sep 21, 2026 31 dates
Cape Town, South Africa 10 days Aug 10, 2026 52 dates
Dar es Salaam, Tanzania 10 days Jul 20, 2026 26 dates
Dubai, UAE 10 days Jul 13, 2026 52 dates
Istanbul, Turkey 10 days Aug 24, 2026 16 dates
Kampala, Uganda 10 days Jul 13, 2026 31 dates
Kigali, Rwanda 10 days Aug 10, 2026 52 dates
Kuala Lumpur, Malaysia 10 days Jul 27, 2026 31 dates
Mombasa, Kenya 10 days Jul 13, 2026 52 dates
Pretoria, South Africa 10 days Aug 10, 2026 52 dates
Singapore 10 days Jul 13, 2026 31 dates
Zanzibar, Tanzania 10 days Aug 3, 2026 16 dates

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 SurveyCTO, GIS, NVIVO and R

DURATION

2 Weeks

LEARNING OBJECTIVES

·         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 SurveyCTO

·         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

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.

TOPICS TO BE COVERED

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 to SurveyCTO

·         Introduction and Key Concepts

·         Overview of ODK and Kobotolbox

·         Advantages of SurveyCTO

·         Key Features of SurveyCTO

·         Case studies on use of SurveyCTO

Module 5:SurveyCTO  Server

·         Components of SurveyCTO

·         Data aggregation, storage, and dissemination

·         Setting up a SurveyCTO server

·         Managing users & user roles

Module 6:Setting Up SurveyCTO  Collect App

·         Installing SurveyCTO collect from google play store

·         Configuring SurveyCTO collect app

·         SurveyCTO   Collect Application  Interface

Module 7:SurveyCTO Online Form builder

·         Creating a form

·         Input types

·         Adding question to Form

·         Form logics

·         Import  and export forms

Module 8:Building Forms using XLSForms

·         Introduction to xlsform designer

·         Components of XlSForm

·         Question types

·         Handling constraints and required options

·         Form skip logic

·         Form Operators and Functions

·         Grouping Questions

·         Settings Worksheet

·         Importing xlsforms to surveyCTO server

Module 9:Using SurveyCTO  Collect

·         Managing forms in SurveyCTO Collect

·         Collecting GPS data

·         Submitting data to  SurveyCTO Server

Module 10:Monitoring Data with SurveyCTO Data Explorer

·         Monitoring Submission statistics

·         Monitoring Form submissions and dataset

·         Reviewing and correcting incoming data

·         Summarize data submitted for individual fields

·         Summarize the empirical relationships between field

Module 11:Data Management

·         Exporting &Exporting data from SurveyCTO as CSV via SurveyCTO Sync

·         Importing SurveyCTO – CSV file into statistical applications

·         Downloading data directly from SurveyCTO

Module 12:Visualizing Geographic Data

·         Exporting GPS Coordinates to Google maps and Google Earth

·         Exporting GPS data for Mapping/Visualizing

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

·         All our courses can be Tailor-made to participants needs

·         The participant must be conversant with English

·         Presentations are well guided, practical exercise, web based tutorials and group work. Our facilitators are expert with more than 10years of experience.

·         Upon completion of training the participant will be issued with Foscore development center certificate (FDC-K)

·         Training will be done at Foscore development center (FDC-K) center in Nairobi Kenya. We also offer more than five participants training at requested location within Kenya, more than ten participant within east Africa and more than twenty participant all over the world.

·         Course duration is flexible and the contents can be modified to fit any number of days.

·         The course fee includes facilitation training materials, 2 coffee breaks, 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.

·         Accommodation, pickup, freight booking and Visa processing arrangement, are done on request, at discounted prices.

·         One year free Consultation and Coaching provided after the course.

·         Register as a group of more than two and enjoy discount of (10% to 50%) plus free five hour adventure drive to the National game park.

·         Payment should be done two week before commence of the training, to FOSCORE DEVELOPMENT CENTER account, so as to enable us prepare better for you.

·         For any enquiry to: training@fdc-k.org or +254712260031

·         Website:www.fdc-k.org

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training@fdc-k.org • +254 712 260 031 • Nairobi, Kenya