[100% Off] Stata Mastery: Practical Data Analysis &Amp; Interpretation
Hands-On STATA: Practical Application & Clear Interpretation
What you’ll learn
- Students will be able to navigate the STATA interface and use its basic commands.
- Students will demonstrate the ability to import and manage datasets within STATA.
- Students will perform descriptive and inferential statistical analyses using STATA.
- Students will interpret statistical results and understand their implications.
- Students will create and customize graphs and charts to present data effectively.
Requirements
- Basic knowledge of Using computer.
Description
Course Description
This course provides a comprehensive introduction to STATA, a powerful statistical software widely used in various fields such as economics, sociology, political science, and public health. The course focuses on the practical application of STATA, covering data management, statistical analysis, and interpretation of results. Students will learn how to perform a range of statistical tests, create meaningful visualizations, and draw valid conclusions from their data. Through hands-on exercises and real-world examples, students will develop the skills necessary to effectively use STATA for their research and professional needs.
Course Objectives
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To provide students with a thorough understanding of the STATA interface and its functionalities.
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To teach students how to import, manage, and manipulate datasets in STATA.
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To equip students with the knowledge to perform a variety of statistical tests and analyses using STATA.
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To enable students to interpret and communicate the results of their statistical analyses effectively.
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To develop students’ ability to create and customize data visualizations in STATA.
Introduction to STATA
Overview of STATA
Installation and setup
Navigating the STATA interface
Basic commands and syntax
Data types and structures in STATA
Data Management in STATA
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Importing data from various sources (Excel, CSV, etc.)
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Data cleaning and preparation
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Data transformation (sorting, merging, reshaping)
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Handling missing data
Descriptive Statistics
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Summary statistics (mean, median, mode, etc.)
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Frequency distributions and cross-tabulations
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Measures of dispersion (variance, standard deviation, etc.)
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Data visualization (histograms, bar charts, pie charts)
Inferential Statistics I
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Hypothesis testing
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t-tests (one-sample, independent, paired)
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Chi-square tests
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Analysis of variance (ANOVA)
Inferential Statistics II
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Correlation analysis
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Simple linear regression
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Multiple regression analysis
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Assumptions and diagnostics for regression models
Advanced Statistical Tests
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Logistic regression
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Factor analysis
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Time series analysis
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Panel data analysis
Estimating Models in STATA
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Detecting Multicollinearity
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Solution to Multicollinearity
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Stationarity of Time Series
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Stationarity of Panel data
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Converting non-stationary series to Stationary
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R-Sqaure
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Auto-Correlation
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Removal of Auto-Correlation
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Johansen-cointegration Test
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Granger Causality Test
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VAR model
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Forecasting in VAR model
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VECM model
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Fixed Effect
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Random Effect
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Hausman Test
Preparing Reports and Documentation
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Creating tables and reports in STATA
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Documenting and annotating your work
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Best practices for reproducible research
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Sharing and collaborating on STATA projects
Special Topics in STATA
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Survey data analysis
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Handling complex survey designs
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Advanced econometric techniques
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Customizing STATA with user-written commands
Review and Final Project
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Review of key concepts and techniques
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Q&A and troubleshooting
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Final project presentations
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Course wrap-up and feedback
