Short Course on Data Analysis, Results interpretation, Presentation and Reporting

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

· Ext 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)

TRAINING CUSTOMIZATION

This training can also be customized for your institution upon request. You can also have it delivered your preferred location.

For further inquiries, please contact us through Mobile: +254 732 776 700/+254759285295 or Email: [email protected]

REQUIREMENTS

· Participants should be reasonably proficient in English. During the trainings, participants should come with their own laptops.

TRAINING FEE

· The course fee covers the course tuition, training materials, two break refreshments, lunch, and study visits.

ACCOMMODATION

· Accommodation is arranged upon request. For reservations contact us through

· Mobile: +254732776700 / +254759285295

or Email: [email protected]