There's been a rise in the amount of information gathering effort, for example, Health Surveys, Demographic, Socio-Economic, and baseline surveys, Employees, clients and also seller pleasure surveys, as well as opinion polls, everything meant to provide information during decision making.

It's crucial that these initiatives go beyond just producing brand new information from data but to improve human judgment on actual development contexts. Just how can businesses better handle the method of transforming the possibility of information science to positive development outcomes .The course is customized to place all of this significant factor into perspective. After completing the training, the participants will have the needed skills to create accurate, reliable, and cost-effective data and accounts which are friendly and useful during decision making.

NVIVO and R will be used.

DURATION: 10 Days

Objectives of Training on Data Analysis Using NVIVO and R

Understand as well as appropriate use of statistical concepts and terms

• Design and also Implement universally appropriate Surveys

• Convert information into different formats using the correct software

• Strong base in basic statistical concepts

• Build user-friendly details visualizations

• Perform hypothesis testing

• Use the survey data to write reports

• Put techniques to enhance data need and also use when making decisions

WHO CAN ATTEND?

This program targets participants with an elementary understanding of Statistics coming from Agriculture,Food Security, Economics, Nutrition, Education, Public or medical health experts among individuals that currently have a little statistical information, but want to be knowledgeable with the principles and uses of statistical modeling.

COURSE TOPICS

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:

o    ODK Build

o    Koboforms

o    PurcForms

·         Hands-on Exercise

Module 6:Preparing the mobile phone for data collection

·         Installing applications: ODK Collect

o    Using Google play

o    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

o    Required questions

o    Constraining responses

o    Skip: Asking Relevant questions

o    The specify other

·         Grouping questions

o    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