Learn multiple regression analysis main concepts from basic to expert level through a practical course with Python.
Master key concepts and practical skills through structured learning modules. By completing this curriculum, you'll gain valuable expertise applicable to real-world scenarios.
Define stocks dependent or explained variable and calculate its mean, standard deviation, skewness and kurtosis descriptive statistics.
Outline rates, prices and macroeconomic independent or explanatory variables and calculate their descriptive statistics.
Analyze multiple regression statistics output through coefficient of determination or R square and adjusted R square metrics.
Examine multiple regression analysis of variance through regression, residuals and total degrees of freedom, sum of squares, mean square error, regression F statistic and regression p-value.
Review multiple regression coefficients through their values, standard errors, t statistics and regression coefficients p-values.
This comprehensive Multiple Regression Analysis with Python curriculum is designed to take you from foundational concepts to advanced implementation. Each module builds upon the previous, ensuring a structured learning path that maximizes knowledge retention and practical application.
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What you need before starting this Multiple Regression Analysis with Python course:
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Everything you need to know about this online course, from duration to certification
Course Instructor
Diego Fernandez
Expert instructor with industry experience
Course Language
English
All materials in English
This online course offers comprehensive training with expert instruction, practical exercises, and a certificate of completion. Join thousands of students advancing their careers through quality online education.
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