Mulago, Collage of Health Sciences Kampala (UG) 

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STATA SOFTWARE FOR DATA ANALYSIS (BEGINNERS)

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About Course

Course Overview

Unlock the power of data analysis with our comprehensive course on utilizing Stata for beginners. Led by the seasoned tutor, Mr. Okello Isaac Opio, this online training program provides a hands-on and practical approach to mastering Stata software. Whether you’re a novice or looking to enhance your skills, this course is designed to equip you with the essential tools for efficient data analysis.

Course/Training Objectives
• Acquire a solid understanding of Stata software, covering its core features for efficient data analysis.
• Familiarize yourself with Stata’s interface.
• Develop practical skills such as typing commands, accessing online help, and loading sample data files.
• Master fundamental statistical techniques, including descriptive statistics, tables, and Graphs.
• Learn easy hacks and tricks to master STATA fast.
• Cultivate hands-on experience in project structuring, log file utilization, and basic data analysis procedures.

Mode of Training
Online sessions ensure flexibility, allowing participants to learn at their own pace. For any inquiries, please contact us at info@daliteresearch.com.

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What Will You Learn?

  • Acquire a solid understanding and practical skills of Stata software, covering its core features for efficient data analysis for all beginners.

Course Content

Lesson 1: Overview of Stata Software
• Stata Overview: A robust statistical package with data management, statistical techniques, and tools for tables and graphs. • Versions: Includes Stata/BE, Stata/SE, and Stata/MP catering to various data sizes and computational needs. • Stata/MP: The fastest edition of Stata (for quad-core, dual-core, and multicore/multiprocessor computers) that can analyze the largest datasets. Stata/SE: Standard edition; for larger datasets. Stata/BE: Basic edition; for mid-sized datasets.

  • Overview of Stata Software
    12:20
  • Lesson 1 Quiz

Lesson 2: Understanding Stata Software Interface
• Interface Components: Consists of five docked windows—Command, Results, History, Variables, and Properties. • GUI and Command Language: Stata's GUI allows menu selection, but command language is recommended for reproducibility.

Lesson 3: Mastering STATA commands & Getting Help
Typing Commands • Case Sensitivity: Stata commands are case-sensitive and can be abbreviated. • Display Command: Utilize the display command for calculations. Getting Help • Online Help: Access help with the help command, useful for command and function information. • Search Command: Use search for documentation exploration.

Lesson 4: Dataset Loading & Data Exploration
Loading a Sample Data File • Loading Data: Utilize sysuse to load sample data files. • Dataset Exploration: Use describe for dataset information. Descriptive Statistics • Summary Statistics: Use commands like summarize to obtain descriptive statistics. • Graphical Representation: Create scatterplots with graph twoway scatter command.

Lesson 5: How To Effectively Use Stata (Hacks & Tricks)
Using Stata Effectively • Project Organization: Create a project directory for better organization. • Log File Usage: Open a log file (log using filename, text replace) to maintain a record of results. • Do File Best Practice: Use a do file for scripting and documentation. • Comments and Annotations: Enhance code readability with comments and annotations.

Lesson 6: Understanding Stata Command Syntax
Structure: The Stata command syntax follows a structured format, where bold indicates keywords and square brackets denote optional elements: [by varlist:] command [varlist] [=exp] [if exp] [in range] [weight] [using filename] [,options] Syntax Elements: 1. command: • The essential element representing the action, usually an action verb. • Commands are case-sensitive; for example, "describe" and "Describe" are distinct. • Commands can be abbreviated, with required letters underlined (e.g., "regress" can be abbreviated to "reg"). 2. varlist: • Follows the command and includes one or more variable names. • Variable names are case-sensitive, and abbreviations must be unique to avoid ambiguity. • Wildcards (e.g., v*) or ranges (e.g., v101-v105) can be used in variable lists. 3. =exp: • Found in commands generating new variables, such as "generate log_gnp = log(gnp)." 4. weight: • Some commands support weights; type "help weights" for more information. 5. using filename: • Introduces a file name, allowing data input from various sources (local, network, internet). 6. options: • Follow a comma and vary based on the command. • Type "help command" to obtain a list of available options. 7. by varlist: • A powerful feature instructing Stata to repeat the command for each group of observations defined by distinct values in the specified variables. • Requires the command to be "byable," and data must be sorted by grouping variable(s) or use "bysort."

Lesson 7: Summary & Conclusion
What have we learnt? And what haven't we learnt?

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