Stata is a complete statistical software package for data management and statistical data analysis. Results from its analysis can easily be presented in both tables and graphs. It comprises a collection of data functions that range from simple to advanced application. The software is very popular with data manipulation, cross sectional data analysis, panel data analysis, forecasting, time series analysis, survival analysis, longitudinal survey methods, structural equation modeling and simulations. The software can be used via a graphical user interface (where users interact with menus, icons and dialog boxes) or a command-line interface (using its very intuitive programming language). The software is supported by a very active user community that not only offer dedicated support but also develop new packages that continuously improves the software capabilities. This five days course is designed to enhance participants’ abilities of using the software. By the end of the training sessions, participants would become intermediate and advanced level users of the software.

DURATION

5 Days

LEARNING OBJECTIVES

By the end of the training, you will be able to:

Understand both descriptive and inferential statistics

Understand various data collection techniques and data processing methods and use mobile phones for data collection(Open data Kit)

Use important functionalities in Stata that relate to data manipulation and management.

Create and manipulate graphs and figures in Stata

Use Stata effectively for analyzing quantitative data descriptively.

Use Stata effectively for analyzing quantitative data using inferential statistics.

Keep records of your work and create reproducible analyses.

Export the results of analyses into word processing programs such as Microsoft Word.

TOPICS TO BE COVERED

Module 1: Introduction

Introduction to Stata

Introduction to Statistics Concepts

Concepts and Software and technologies for Data Collection and Processing

Stata Basics: Program window features, Data Structures and Types of Variables

Data Management using Stata

Output Management

Basics of stata programming

Introduction to Mobile Data gathering

Benefits of Mobile Applications

Data and types of Data

Introduction to common mobile based data collection platforms

Managing devices

Challenges of Data Collection

Data aggregation, storage and dissemination

Questionnaire Design

Getting started in ODK

Types of questions

Data types for each question

Types of questionnaire or Form logic

Extended data types geoid, image and multimedia

Survey Authoring and Preparation of mobile phone for data collection

Survey Authoring

Design forms using a web interface: ODK Build, Koboforms, PurcForms

Preparing the mobile phone for data collection

Installing applications: ODK Collect (using Google play)

Designing forms and advanced survey authoring

Designing forms manually: Using XLS Forms

Introduction to XLS forms syntax

New data types

Notes and dates

Multiple choice Questions

Multiple Language Support

Hints and Metadata

Hands-on Exercise

Advanced survey Authoring

Conditional Survey Branching

Required questions

Constraining responses

Skip: Asking Relevant questions

The specify other

Grouping questions

Skipping many questions at once (Skipping a section)

Repeating a set of questions

Special formatting

Making dynamic calculations

Hosting survey data

Online Hosting survey data (ODK Aggregate, Formhub, ona.io and KoboToolbox

Module 2: Descriptive Statistics

Measures of Variability and Central Tendency

Describing quantitative data

Describing qualitative data (Tabulating data with Stata)

Stata Graphics

Graphing quantitative data

Graphing qualitative data

Module 3: Correlation, Chi-square and mean comparison analysis

Correlation

Subgroup Correlations

Scatterplots of Data by Subgroups

Overlay Scatterplots

Chi-Square

Goodness of Fit Chi Square All Categories Equal

Goodness of Fit Chi Square Categories Unequal

Chi Square for Contingency Tables

Comparing Means

One Sample t-tests

Paired Sample t-tests

Independent Samples t-tests

Comparing Means Using One-Way ANOVA

Comparing Means Using Factorial ANOVA

Factorial ANOVA Using GLM Univariate

Simple Effects

Module 4: Regression Analysis and Nonparametric Statistics

Regression Analysis

Assumptions of selected types of regression

Linear regression; Binary logistic regression; ordered logistic regression; multinomial logistic regression and Poisson regression

Nonparametric Statistics

Mann-Whitney Test

Wilcoxon’s Matched Pairs Signed-Ranks Test

Kruskal-Wallis One-Way ANOVA

Friedman’s Rank Test for k Related Samples

Module 5: Longitudinal/panel and Time series Analysis

Panel data analysis

Introduction to panel data

Longitudinal/panel data analysis

Time series Analysis

Basic elements of time-series analysis

Managing and summarizing time-series data

Time series data analysis

Introduction to forecasting

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: +254 759 285 295. You can also email us on: [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: +254 759 285 295 or Email: [email protected]

PAYMENT

Payment should be transferred to FineResults Research Services bank account before commencement of training. Send proof of payment through the email: [email protected]

CANCELLATION POLICY

All requests for cancellations must be received in writing.
Changes will become effective on the date of written confirmation being received.

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FineResults Research Services offers training solutions to individuals, communities, governments and civil society organizations, both local and international.

We also provide application-oriented and field-based consultancy services in all aspects of research and evaluations from inception to completion. This includes research designs, designing monitoring and evaluations systems, technical reviews, programme evaluations, questionnaire validation, data collection, data capture, data analysis and report writing. FineResults Research Services is a limited company incorporated under the laws of Kenya. Its head office is in Nairobi Kenya.

The organization has a wide range of experience working with both local and international organizations in both consultancies and capacity building in Africa and beyond.

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