International Training on Research Design & Methodology, Data management, Analysis, Inferences and Reporting

INTRODUCTION

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All researchers are based on some underlying philosophical assumptions about what constitutes valid research and which research design and methodology method(s) is/are appropriate for the development of knowledge in a given research. In order to conduct and evaluate any research, it is therefore important to come up and embrace appropriate Research Design & Methodology, Data Management, Analysis, Inferences and Reporting standards for decision making. Without appropriate research design and methodology, the entire process is distorted interfering with the integrity of data collect leading to an inaccurate and inappropriate analysis of research findings. Improper statistical analyses distort scientific findings, mislead casual readers, and may negatively influence the public perception of research. These training aims introduce and enhance the participants’ knowledge of research design & methodology, data management, analysis, inferences and reporting of research findings.  The participants will be exposed to Mobile Based Data collection using ODK, use of Ms-Excel and Statistical analysis software of interest (Stata/SPSS/R).

FOR WHOM IS THIS TRAINING INTENDED?

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This is a general training targeting participants from Social, Agriculture, Economics, Food Security and Livelihoods, Nutrition, Education, Medical or public health professionals among others who wish to be conversant with the concepts of Statistics, Research Design & Methodology, Data collection using ODK, use of GIS for mapping, Data Management, Analysis using MS-Excel, Stata/SPSS/SAS/R Softwares and Inferences and Reporting. No prior knowledge is required.

TRAINING DURATION

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10 days.

TRAINING OBJECTIVES

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The training is aimed at introducing and equipping participants with skills in;

• Planning for selecting appropriate research design
• Prevention of potential errors in research planning stage and control 
• Sample Size Determination and use of sampling techniques
• Designing survey tools (e.g. Questionnaires) and use om mobile based data collection techniques (ODK)
• GIS Mapping
• Data Management and Analysis using Ms-Excel
• Data Entry, Management, and Manipulation using Stata/SPSS/SAS/R
• Importing/ exporting datasets
• Quality checks of datasets
• Generating tables and graphs and creating a syntax for the output (Stata/SPSS/SAS/R)
• Analysis of Survey data using inferential statistics using Stata/SPSS/SAS/R and making Inferences
• Report writing

TRAINING CONTENTS

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Module 1: Statistical/Recap to Statistics Concepts

Statistics concepts

• Types of data  (qualitative and Quantitative data)

• Data Analysis Techniques
• Descriptive Statistics and Inferential Statistics
• Common inferential statistics
• The core functions of inferential statistics

Research Methodology

• Research Methodology process.
• Components of research methodology.

Module 2: Research Design and Data Collection tools & techniques

Research Design

• Definition of research design
• Types of research designs

• Benefits of various research design to a study
• Selecting Appropriate research design (Informed by the scope of a project)
• Potential errors in research and how to prevent them in research planning stage and control 
• Exercise: Determination of Appropriate Research Design for a project.

Target Population, Sample Size, and Sampling techniques

• Target population identification
• Sample size determination
• Different types of Sampling techniques, their advantages, and disadvantages and when to use each

Data Collection Techniques and tools for a survey

• Definition of data collection techniques
• Different techniques for data collection, they advantages, and disadvantages
• Tools for data collection
• Designing survey questionnaires (based on study objectives)
• Pretesting research tools for Validity and Reliability

Exercise: Developing research methodology and planning for survey data collection exercises

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

• Introduction to mobile phone data collection
• Common mobile based data collection platforms
• Advantages and challenges of Mobile Applications
• Challenges 
• Introduction to Open Data Kit ODK
• Components of Open Data Kit (ODK)
• Collecting data using ODK
• GIS Mapping
• Exercise: use of ODK for data collection exercises and GIS Mapping

Module 4:  Data Management and Analysis using Ms-Excel

• Introduction to Excel for Data Processing and Analysis
• Exploring survey data using Excel
• Tabulating and Graphing survey data using Excel
• Pivot tables
• Tabulating and Graphing survey data using Excel
• Exercise:  Tabulating and Graphing survey data using Excel and preparing pivot tables

Module 5: Data Management and Analysis using statistical Softwares: (Stata/ SPSS/R)

• Introduction to the software

- Stata/ SPSS/SAS/R

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

• Importing/ exporting datasets

• Defining and labeling data and variables
• Creating, transforming, recoding variables
• Generating new variables
• Creating New datasets, sorting and ordering, and modification
• Quality checks of datasets: Identify duplicate observations
• Merging and Appending data files
• Exercises: Data Entry, Management and Manipulation and quality checks for survey data

Module 7: Graphic, tabulations and output management using Stata/SPSS/SAS/R

• Introduction to output Management using
• Tabulating data
• Basics of Graphing
• Customizing Graphs
• Exporting graphics and tabulations.
• Syntax for outputs
• Exercises: generating tables and graphs and creating a syntax for the output

Module 8: Analysis of Survey data using inferential statistics using Stata/SPSS/SAS/R and making Inferences

• Introduction/recap of inferential statistics
• Recap/Introduction to Statistical Inference, their applications and underlying conditions for their use;
• Measures and tests of association
• Tests of difference
• Hypothesis Testing  and Inference
• Correlation analysis
• Students T test
• Exercises: generating and interpreting inferential statistics

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

• Types of regression analysis model and their application.
• Generating regression models

-         Linear regression (simple linear, multiple linear)

-         Logistic Regression

• Exercise: Generating regression models

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

• Writing strategies for simple and advanced levels survey reports
• Report structures
• Considerations before writing the report
• Writing a survey report
• Appropriate language use
• Making conclusions and recommendations
• Communication and dissemination
• Decision making based on findings report
• Exercise: Preparing a report