Regression series (10 videos)
Regression is a statistical technique used to model the relationship between a dependent variable and one or more independent variables. It involves calculating the sum of squared errors (SSE), sum of squared regression (SSR) and sum of squared total (SST) to determine the R-squared value. Degrees of freedom, adjusted R-squared and non-linear relationships are also discussed in the series. Additionally, logarithms and advanced regression techniques are explored. ▼
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Course Feature
Cost:
Free
Provider:
Youtube
Certificate:
Paid Certification
Language:
English
Start Date:
On-Demand
Course Overview
❗The content presented here is sourced directly from Youtube platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.
Updated in [February 21st, 2023]
Learners can learn the fundamentals of regression from this course. This includes understanding the concepts of SSE, SSR, SST, R-squared, errors (ε vs. e), degrees of freedom, adjusted R-squared, non-linear relationships, logarithms, categorical X variables, interaction terms, logit models, regression assumptions, heteroskedasticity, multicollinearity, and autocorrelation.
Learners can also learn how to apply these concepts to real-world data. This includes understanding how to interpret regression output, how to identify and address issues such as multicollinearity and heteroskedasticity, and how to use logarithms and interaction terms to improve the accuracy of the model.
Finally, learners can gain an understanding of the underlying mathematics of regression. This includes understanding the mathematics behind SSE, SSR, SST, R-squared, errors (ε vs. e), degrees of freedom, adjusted R-squared, non-linear relationships, logarithms, categorical X variables, interaction terms, logit models, regression assumptions, heteroskedasticity, multicollinearity, and autocorrelation.
Overall, this course provides learners with a comprehensive understanding of regression and its applications. It covers the fundamentals, practical applications, and underlying mathematics of regression, giving learners the knowledge and skills they need to effectively use regression in their own data analysis.
[Applications]
After completing this course, learners should be able to apply the concepts of regression to their own data sets. They should be able to understand the different types of regression models, the assumptions of each model, and the implications of errors and heteroskedasticity. They should also be able to interpret the output of regression models and use logarithms and interaction terms to create more complex models. Finally, learners should be able to identify and address issues of multicollinearity and autocorrelation.
[Career Paths]
1. Data Scientist: Data Scientists use regression models to analyze large datasets and uncover trends and patterns. They use these insights to develop predictive models and make data-driven decisions. As data becomes increasingly important in the business world, the demand for Data Scientists is growing rapidly.
2. Business Analyst: Business Analysts use regression models to identify trends and relationships between different variables. They use this information to make decisions about how to improve business operations and increase profits. As businesses become more data-driven, the demand for Business Analysts is also increasing.
3. Machine Learning Engineer: Machine Learning Engineers use regression models to develop algorithms that can learn from data and make predictions. They use these algorithms to create automated systems that can make decisions without human intervention. As machine learning becomes more popular, the demand for Machine Learning Engineers is also increasing.
4. Statistician: Statisticians use regression models to analyze data and draw conclusions. They use these insights to develop models that can be used to make predictions and inform decisions. As data becomes increasingly important in the business world, the demand for Statisticians is also growing.
Course Provider
Provider Youtube's Stats at AZClass
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