Overview

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Gain a solid grounding in statistical reasoning and learn the essentials of data management and regression analysis using Stata. This course introduces core statistical concepts and guides learners through the basics of working with data and performing foundational regression techniques. This course covers the fundamental principles of research and statistics, providing a clear understanding of statistical inference, probability, and objectivity in quantitative research. Learners will become proficient in using Stata for data entry, management, and exploration, and will develop skills in simple and multiple regression analysis. By the end of the course, participants will be able to confidently manage datasets and perform essential statistical analyses using Stata. The course combines clear explanations of statistical concepts with practical demonstrations in Stata, using real-world examples to reinforce learning. Learners progress step-by-step from foundational theory to hands-on application, ensuring both conceptual understanding and practical competence. This course is part one of a three-course Specialization designed to build a complete and cohesive understanding of the subject. While it offers valuable skills on its own, you'll gain the most benefit by progressing through all three courses as a structured learning journey. This course is based on Applied Statistics Using Stata, by Mehmet Mehmetoglu and Tor Georg Jakobsen. Copyright ©2022 by Sage Publications Limited. All rights reserved, including rights for text and data mining and training of artificial technologies or similar technologies. Published by Sage Publications Limited, London. Used by arrangement with Sage Publications Limited.

Syllabus

Research and Statistics
- This module covers the foundational elements of statistical research, including methodology, inference, and research design. Learners will gain an understanding of how to apply statistical concepts effectively, interpret data, and avoid common pitfalls in quantitative analysis. It also explores the importance of objectivity and critical thinking in research.
Introduction to Stata
- This module provides an introductory overview of Stata, covering its interface, data entry, and import techniques. Learners will gain hands-on experience with data management commands, descriptive statistics, and basic bivariate inferential statistics. The module aims to build foundational proficiency in using Stata for data analysis.
Simple (Bivariate) Regression
- This module provides an in-depth understanding of simple linear regression, including the principles of OLS estimation, assessing model fit, and conducting hypothesis tests. Learners will develop practical skills in using Stata to analyze relationships between two variables and make data-driven predictions. The content emphasizes both theoretical foundations and real-world applications in statistical modeling.
Multiple Regression
- This module covers the fundamentals of multiple regression analysis, including model building, evaluation, and interpretation using Stata. Learners will gain practical skills in assessing model fit, understanding statistical control, and making predictions based on multiple variables. The content provides a foundation for applying regression techniques in real-world data analysis.