Training Course On Research Design, Mobile Data Collection, Mapping And Data Analysis Using Nvivo And Python

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Whatapp

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 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 PYTHON

COURSE OBJECTIVES

At the end of course participants should be able to:

·        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

·        Python for Data Science and Machine

·        Spark for Big Data Analysis

·        Implement Machine Learning Algorithms

·        Numbly for Numerical Data

·        Pandas for Data Analysis

·        Matplotlib for Python Plotting

·        Seaborn for statistical plots

·        interactive dynamic visualizations

·        SciKit-Learn for Machine Learning Tasks

·        K-Means Clustering, Logistic Regression and Linear Regression

·        Random Forest and Decision Trees

·        Natural Language Processing and Spam Filters

·        Neural Networks

·        Support Vector Machines

·        Write reports from survey data

·        Put strategies to improve data demand and use in decision making

DURATION

10 Days

WHO SHOULD ATTEND

The course targets 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.

COURSE CONTENT

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)

THE END

Looking forward to your attendance.