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.
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
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
Challenges of Data Collection
Data aggregation, storage and dissemination
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
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
Advanced survey Authoring
Conditional Survey Branching
Skip: Asking Relevant questions
The specify other
Skipping many questions at once (Skipping a section)
Repeating a set of questions
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)
Graphing quantitative data
Graphing qualitative data
Module 3: Correlation, Chi-square and mean comparison analysis
Scatterplots of Data by Subgroups
Goodness of Fit Chi Square All Categories Equal
Goodness of Fit Chi Square Categories Unequal
Chi Square for Contingency Tables
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
Module 4: Regression Analysis and Nonparametric Statistics
Assumptions of selected types of regression
Linear regression; Binary logistic regression; ordered logistic regression; multinomial logistic regression and Poisson regression
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
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 or Email: email@example.com
Participants should be reasonably proficient in English. During the trainings, participants should come with their own laptops.
The course fee covers the course tuition, training materials, two break refreshments, lunch, and study visits.
Accommodation is arranged upon request. For reservations contact us through Mobile: +254 732 776 700 or Email: firstname.lastname@example.org
Payment should be transferred to FineResults Research Limited bank before commencement of training. Send proof of payment through the email: email@example.com
• 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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