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. course is tailored to put all these important considerations 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 STATA
Introduction to statistical concepts
Descriptive Statistics
Inferential statistics
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
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
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
Design forms using a web interface using:
ODK Build
Koboforms
PurcForms
Hands-on Exercise
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
Notes and dates
Multiple choice Questions
Multiple Language Support
Hints and Metadata
Hands-on Exercise
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
ODK Aggregate
Formhub
ona.io
KoboToolbox
Uploading forms to the server
Configuring ODK Aggregate on a local server
Downloading data
Manual download (ODK Briefcase)
Using the online server interface
Introduction to GIS for Researchers and data scientists
Qualitative Data
Types of Qualitative Data
Sources of Qualitative data
Qualitative vs Quantitative
NVivo key terms
The NVivo Workspace
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
NVIVO Key terms
NVIVO interface
NVIVO workspace
Use of NVIVO ribbons
Creating new projects
Opening and Saving project
Working with Qualitative data files
Importing Documents
Merging and exporting projects
Managing projects
Working with different data sources
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
Source classifications
Case classifications
Node classifications
Creating Attributes within NVivo
Importing Attributes from a Spreadsheet
Getting Results; Coding Query and Matrix Query
Data-driven vs theory-driven coding
Analytic coding
Descriptive coding
Thematic coding
Tree coding
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
Queries for textual analysis
Queries for exploring coding
Content Analysis; Descriptive, interpretative
Narrative Analysis
Discourse Analysis
Grounded Theory
Comparing analysis results with research questions
Summarizing finding under major categories
Drawing conclusions and lessons learned
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
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
Qualitative report format
Reporting qualitative research
Reporting content
Interpretation
Research design
Samples and populations
Comparison of experimental and non-experimental designs
Exploring variable types
Datasets
Commands
Working with variables in Stata
Basic analysis using Stata
Classifying different charts and processing them using STATA
Understanding the Graph command syntax
Graphs for categorical Vs Numeric variables
Managing chart output in STATA
Multivariate charting
One Sample T Test
Independent Samples T Test
Paired Samples T Test
One-Way ANOVA
Chi-Square test
Pearson's Correlation
Spearman's Rank-Order Correlation
Linear Regression
Multiple Regression
Logistic Regression
Ordinal Regression
Exploration of panel data
Fixed effects model/LSDV
Random effects model
Choosing the appropriate model
Introduction to time series analysis using Stata
Plotting a time series
Seasonal differences
Auto correlations
Forecast models in Stata
Econometric Analysis of cross-sectional data
Econometric Analysis of panel data
Econometric Analysis of time-series data
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
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
Workflow use commands in STATA
Manage, edit and structure large databases in STATA
Generating descriptive statistics in STATA
Creating powerful publication-quality graphs in STATA
Data Analysis/Estimations in STATA
Write reports from survey data
Put strategies to improve data demand and use in decision making
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