Research Design, Data Management, Analysis and Use

INTRODUCTION

The type of research design, philosophical assumptions, and methodologies used by a researcher are key determinants of the outcome and the validity of a particular research. In order to carry out and evaluate any research, it is necessary to embrace and come up with appropriate data management strategies, analysis, design, methodology, inferences, and reporting standards for informed decision making. Without appropriately choosing the best of these elements, the entire research process can be distorted leading to incorrect data and inaccurate reporting. What is more, inaccurate scientific findings are bound to mislead readers and may even negatively impact the perception of research in the eyes of the public.

The aim of their training is to ensure that the participants gain knowledge on key elements of research including design & methodology, analysis, data management, inferences and reporting of research findings

The course targets participants who wish to carry out research or gain essential skills on how to conduct research including applicants from the following fields: Social, Food Security and Livelihoods, Agriculture, Medical or public health professionals, Education, Economics, Nutrition, among others.  

TRAINING DURATION

10 days.

Course Outcomes

This training equips participants with the following skills:

• Analysis of Survey data using inferential statistics (Stata/SPSS/SAS/R) and making Inferences

• Data Entry, Manipulation, and Management using Stata/SAS/R/SPSS

• Data Management and Analysis using MS-Excel

• Designing survey tools (e.g. Questionnaires) and use om mobile based data collection techniques (ODK)

• Generating tables and graphs  (Stata/SPSS/SAS/R)

• GIS Mapping

• Importing/ exporting datasets

• Planning for the selection of appropriate research design

• Quality checks of datasets

• Prevention of potential errors in research planning stage and control 

• Report writing

• Sample Size determination and use of sampling techniques

TRAINING CONTENTS

________________________________________

Module 1: Statistical/Recap to Statistics Concepts

Statistics concepts

• Common inferential statistics

• Data Analysis techniques

• Descriptive Statistics and Inferential statistics

• The core functions of inferential statistics

• Types of data  (qualitative and Quantitative data)

Research Methodology

• Components of research methodology.

• Research Methodology process.

Module 2: Research Design, Data collection tools, and procedures

Research Design

• Definition of research design

• Types of research designs

• Benefits of various research design to a study

• Potential errors in research and how to prevent them in research planning stage and control 

• Selecting Appropriate research design (Informed by the scope of a project)

• Exercise: Determination of Appropriate Research Design

Target Population, Samples and Sampling methods

• Different types of Sampling techniques 

• Target population identification

Data Collection tools and techniques for a survey

• Designing survey questionnaires (based on study objectives)

• Definition of data collection techniques

• Different techniques for data collection

• Pretesting research tools for Validity and Reliability

• Tools for data collection

Exercise: Developing research methodology and formulating for survey data collection 

Module 3: Mobile-Based data Collection using GIS and ODK Mapping

• Advantages and challenges of Mobile Applications

• Challenges 

• Collecting data using ODK

• Common mobile based data collection platforms

• Components of Open Data Kit (ODK)

• GIS Mapping

• Introduction to mobile phone data collection

• Introduction to Open Data Kit ODK

• Exercise: use of ODK for GIS maping and data collection

Module 4:  Management of Data and Data Analysis using Ms-Excel

• Exploring survey data using Excel

• Tabulating and graphing survey data using Excel

• Introduction to Excel for Data processing and Analysis

• Tabulation and displaying survey data using Excel

• Pivot tables

• Exercise:  Graphing and tabulating survey data using Excel 

Module 5: Managing and analysing data using statistical software: (SPSS/Stata/ R)

• Introduction to the software

- SPSS/Stata/ SAS/R

Module 6: Data Entry, Management and Manipulation using SPSS/Stata/ SAS/R

• Creating New datasets, sorting and ordering and modification

• Creating, transforming, recoding variables

• Defining and labeling data and variables

• Generating new variables

• Importing/ exporting datasets

• Merging and appending data files

• Quality checks of datasets: Identify duplicate observations

• Exercises: Data Entry, Manipulation, and Management and quality checks for survey data

Module 7 Tabulation,  Graphics, and output management using SPSS/Stata/ SAS/R

• Advanced graphing

• Basics of graphing

• Customizing graphs

• Exporting graphics and tabulations.

• Introduction to output Management 

• Syntax for outputs

• Tabulating data

• Exercises: generation of tables and graphs and the creaiton of a syntax for the output

Module 8: Analysis of data collected from surveys using inferential statistics  

• Correlation analysis

• Hypothesis Testing  and inference

• Introduction/recap of inferential statistics

• Measures and tests of association

• Recap/introduction to Statistical Inference, their applications and underlying conditions for their use;

• Students T test

• Tests of difference

• Exercises: generation and interpretion of inferential statistics

Module 9:  Regression analysis using SPSS/Stata/ SAS/R and making Inferences:

• Types of regression analysis models

• Generation of regression models

-         Binary regression

-         GLM Model

-         Linear regression (simple linear, multiple linear)

-         Logistic Regression

• Exercise: Generating regression models

Module 10: Report writing for survey findings, Dissemination and Use

• Appropriate language use

• Communication and dissemination

• Considerations before writing the report

• Decision making based on findings report

• Exercise: Preparing a report 

• Making conclusions and recommendations

• Report structures

• Writing a survey report

• Writing strategies for  both simple and advanced levels survey reports