Training course on Research Designing and Data Analysis for Informed Decision Making

Workshop Title: Research Designing and Data Analysis for Informed Decision Making

Dates and registration links

23/01/2023 to  27/01/2023 - https://bit.ly/3TCNR3u

17/04/2023 to  21/04/2023 - https://bit.ly/3VPf98v

10/07/2023 to  14/07/2023 - https://bit.ly/3MSIA5m

16/10/2023 to  20/10/2023 - https://bit.ly/3CY5Cn2

04/12/2023 to  08/12/2023 - https://bit.ly/3sm4g0t

INTRODUCTION

Understanding the appropriate data analysis method, the right interpretation of results is critical in coming up with an evidenced based decision for development. Further, learning the basic recommendations involved in presenting of the results using texts, tables and graphs is essential because it makes it much easier to understand the data under analysis and to promote accurate communication of research outputs. Moreover, well presented research information in the form of texts, tables and graphs not only make research output article easy to understand but also attract and sustain the interest of readers, and ably present complex information. This 5-days course will equip participants with skills necessary in data analysis, data interpretation and presentation.

Duration:

5 days

Who should attend?

Researchers, students, anyone who interested in enhancing his/ her data analysis skills

What you will learn:

• By the end of the training participants will be able to:
• Understand fundamental statistical concepts
• Learn data handling, cleaning and management techniques using the data analyzing software of choice
• Analyze data by applying appropriate statistical techniques
• Learn how to present results using tables, charts and graphs
• Interpret the results
• Learn various parts and contents of research outputs (Research reports, journal articles and policy briefs)

COURSE OUTLINE

Module 1:

Introduction to statistical terms and concepts

Types of research

• Research Process
• Definition of various  statistical concepts
• Descriptive Statistics
• Inferential statistics

Module 2:

 Types of Research Designs

• Definition of research design
• Types of qualitative research designs
• Types of quantitative Research designs
• Mixed method research designs

Module 3:

Descriptive analysis

• Frequencies and percentages
• Measurers of central tendencies (Means, standard deviations, median, mode e.t.c)
• Test statistics (Parametric and non-parametric tests)
• Assumptions of parametric tests
• Tests of independence
• Tests for Goodness of fit
• Test for associations

Module 4:

Regression analysis

• Factors to consider while choosing the appropriate regression models
• Assumptions of simple linear regressions
• How to run Diagnostic tests (Multicollinearity, heteroscedasticity, linearity, autocorrelation etc)
• Simple and multiple linear regressions
• Logistic regressions (Logit and probit models)
• Generalized linear model  regression (Poisson regression)
• Censored regression model and truncated regression models (Tobit models)
• Models to control for sample selection bias (Heckman two stage models

Module 5:

Presentation of results from descriptive analysis and regression models

• Techniques of data and information presentation in textual, tabular, and graphical forms
• Criteria of determining the Methods of presenting results
• Text (narrative) presentation
• Table presentation
• Graphs presentation
• Interpretation of descriptive analysis and regression models results
• Discussing of the results of descriptive analysis and regression models results
• Understanding the outline and content of various research outputs (reports, journal articles and policy brief e.t.c)
• Exercise: drafting of a research output of choice (Journal article, report or policy brief etc)