- TypeTraining or Development Class
- Location Nairobi, kenya,Nairobi,Kenya
- Date 10-10-2022 - 14-10-2022
Research/Science
Business Development
Course title: Result for Data Analysis Results interpretation Presentation and Reporting
Training venue: Nairobi Kenya
Course dates:
08/08/2022 -12/08/2022 : https://bit.ly/3uvBv2F
10/10/2022 - 14/10/2022 : https://bit.ly/3Az3LW6
05/12/2022 - 09/12/2022 : https://bit.ly/3IAeRwd
Contact us through: E: [email protected]; Tel: +254732776700 / +254759285295
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:
Course outline
Module 1: Introduction to statistical terms and concepts
· Research Process
· Definition of various statistical concepts
· Descriptive Statistics
Module 2: Types of Research Designs
Module 3: Descriptive analysis
· 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
Module 4: Regression analysis
· 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)
Module 5: Presentation of results from descriptive analysis and regression models
· 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)