Research Design, Mobile Data Collection, Mapping & Data Analysis Using NVIVO & Python
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 on research design and data analysis using NVIVO and Python, 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.
DURATION: 10 Days
Objectives of Training on Research Design and Data Analysis Using NVIVO and PYTHON
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 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 13: 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 14:Understanding Qualitative Research
· Qualitative Data
· Types of Qualitative Data
· Sources of Qualitative data
· Qualitative vs Quantitative
· NVivo key terms
· The NVivo Workspace
Module 15: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 16:Introduction to NVIVO
· NVIVO Key terms
· NVIVO interface
· NVIVO workspace
· Use of NVIVO ribbons
Module 17: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 18: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 19: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 20: Coding
· Data-driven vs theory-driven coding
· Analytic coding
· Descriptive coding
· Thematic coding
· Tree coding
Module 21: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 22:Queries using NVIVO
· Queries for textual analysis
· Queries for exploring coding
Module 23: Building on the Analysis
· Content Analysis; Descriptive, interpretative
· Narrative Analysis
· Discourse Analysis
· Grounded Theory
Module 24: Qualitative Analysis Results Interpretation
· Comparing analysis results with research questions
· Summarizing finding under major categories
· Drawing conclusions and lessons learned
Module 25: 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 26: 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 27: Report Writing
· Qualitative report format
· Reporting qualitative research
· Reporting content
· Interpretation
Module 28: Introduction to Phython
· Course Intro
· Setup
· Installation Setup and Overview
· IDEs and Course Resources
· iPython/Jupyter Notebook Overview
Module 29:Learning Numpy
· Intro to numpy
· Creating arrays
· Using arrays and scalars
· Indexing Arrays
· Array Transposition
· Universal Array Function
· Array Processing
· Array Input and Output
Module 30: Intro to Pandas
· DataFrames
· Index objects
· Reindex
· Drop Entry
· Selecting Entries
· Data Alignment
· Rank and Sort
· Summary Statistics
· Missing Data
· Index Hierarchy
Module 31: Working with Data
· Reading and Writing Text Files
· JSON with Python
· HTML with Python
· Microsoft Excel files with Python
· Merge and Merge on Index
· Concatenate and Combining DataFrames
· Reshaping, Pivoting and Duplicates in Data Frames
· Mapping,Replace,Rename Index,Binning,Outliers and Permutation
· GroupBy on DataFrames
· GroupBy on Dict and Series
· Splitting Applying and Combining
· Cross Tabulation
Module 32:Big Data and Spark with Python
· Welcome to the Big Data Section!
· Big Data Overview
· Spark Overview
· Local Spark Set-Up
· AWS Account Set-Up
· Quick Note on AWS Security
· EC2 Instance Set-Up
· SSH with Mac or Linux
· PySpark Setup
· Lambda Expressions Review
· Introduction to Spark and Python
· RDD Transformations and Actions
Module 33: Data Visualization
· Installing Seaborn
· Histograms
· Kernel Density Estimate Plots
· Combining Plot Styles
· Box and Violin Plots
· Regression Plots
· Heatmaps and Clustered Matrices
Module 34: Data Analysis
· Linear Regression
· Support Vector
· Decision Trees and Random Forests
· Natural Language Processing
· Discrete Uniform Distribution
· Continuous Uniform Distribution
· Binomial Distribution
· Poisson Distribution
· Normal Distribution
· Sampling Techniques
· T-Distribution
· Hypothesis Testing and Confidence Intervals
· Chi Square Test and Distribution
Module 35: 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
Date | Venue | Register |
---|---|---|
22nd to 26th Jan 2024 | Nairobi | |
19th to 23rd Feb 2024 | Mombasa | |
25th to 29th March 2024 | Nairobi | |
22nd to 26th April 2024 | Istanbul | |
20th to 24th May 2024 | Nairobi | |
24th to 28th June 2024 | Dubai | |
22nd to 26th July 2024 | Nairobi | |
26th to 30th Aug 2024 | Nairobi | |
23rd to 27th Sept 2024 | Nairobi | |
21st to 25th Oct' 2024 | Mombasa | |
25th-29th Nov' 2024 | Nairobi | |
16 to 20th Dec 2024 | Nairobi |
Multiple Training Categories
We offer broad training categories suitable for your needs depending on your profession.