Correlation and linear regression with Stata in Arabic
A step-by-step implementation of correlation and linear regression concepts by using STATA in Arabic with real dataset.
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What You Will Learn!
- Identify and understand the concept of correlation analysis.
- How to determine the direction, strength, and significance of the correlation.
- How to apply and interpret correlation analysis.
- How to present the correlation data by a suitable graph through data visualization.
- The concept of linear regression and its relation to correlation.
- Applying and interpreting a simple linear regression analysis with continuous predictor
- Applying and interpreting a simple linear regression analysis with categorical predictor
- Applying and interpreting a simple linear regression analysis with ordinal predictor
- Applying and interpreting a multiple linear regression analysis with different types of predictors
- How to graph and fit the model of linear regression analysis
- Understanding interaction concept
- How to test for interaction between predictors
- How to graph the interaction process
- Post-estimation analysis and how to apply margin and margins-plot with linear regression analysis.
Description
This course will teach you the fundamentals and advanced techniques for performing correlation and linear regression analyses with STATA in Arabic. The course is broken down into five sections.
The first section is an introduction that includes a description of the Framingham dataset, a large real-world dataset that has been used in at least 3000 publications since 1948. Throughout the course, this dataset will be used for real-world applications.
The second part of this course will concentrate on studying and learning how to apply correlation analysis and interpret its three parameters, including direction, strength, and significance, as well as how to choose the appropriate test and make the correct interpretation. Furthermore, for data visualization, you will learn how to use the appropriate graph to represent your data.
The third section of this course will focus on regression analysis and its performance using simple linear regression and multiple linear regression models to answer real-world research questions. As continuous, categorical, and ordinal variables, various types of variables will be used.
The fourth section will go over advanced post-estimation analysis techniques like interaction, margins, and margins plots. Separate videos will demonstrate a specific concept throughout the course, followed by actual STATA and real dataset implementation.
The concluding section will include a summary of the course's essential information.
Who Should Attend!
- Researcher who would like to upgrade their skills and learn new statistical technique in correlation and linear regression analysis by using STATA
- All researchers in the biomedical, epidemiological, and basic science fields.
