Research Design, Mobile Data Collection, GIS Mapping and Data Analysis using NVIVO and R Course

Course Date: 23rd September – 04th, October 2019 for 10 Days

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Click to Download 2019 Course Calendar in PDF

Organizer: Foscore Development Center

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

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 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

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

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

ona.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

  • 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 10 years 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) 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: [email protected] or +254712260031

  • Website: www.fdc-k.org

  • Click to view course outline and register online to attend

  • Click to view Research and Data Analysis courses calendar 2019

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