Statistics for Data Analytics
This course will educate you to comprehend two fundamental statistical concepts, Correlation and Regression, as well as Six Sigma. This course is divided into five components. Correlation, Correlation Analysis, Calculating Correlation Coefficient, Practical Application of Correlation and Regression with an Example, Regression, Significance F and p-values, Coefficients, Residual, and Conclusion make up Section 1. The second section covers regression analysis, as well as the practical application of each regression analysis with an example and the usage of Minitab to do regression analysis. Nonlinear Regression Analysis is covered in Section 3.
This course will teach you how to calculate the correlation coefficient using Karl Pearson's approach, Spearman's Rank Difference Method, and the Method of Concurrent Deviations. Several major Karl Pearson approaches, including as the Direct Method and the Assumed Mean Method, have been thoroughly explored here. Correlation in Grouped Series was also thoroughly described. Both ways with different rankings and situations with the same ranks have been detailed in Spearman's Method, as well as the Method of Concurrent Deviations.
This course offers:
- Flexible deadlines: Reset deadlines in accordance to your schedule.
- Certificate: Earn a Certificate upon completion
- 100% online
- Beginner Level
- Approx. 6.5 hours to complete
- Subtitles: English
Course Rating: 4.1/5
Enroll here: https://www.udemy.com/course/statistics-for-data-analytics/
