About Regression AnalysisLearn More
Regression is a statistical method to measure the effects of variables by considering their simultaneous relationships with each other. The literal meaning of regression is to return to the past, and the name of this method is to use past data to predict the future. The formation and invention of regression methods goes back to the last decade of the 19th century. In 1886, Karl Pearson was able to provide a formula for calculating the correlation coefficient, which, in addition to being innovative, provided a new path in the science of statistics. This formula was the basis of the regression theory. If the Pearson formula shows the correlation between two variables, in the regression theory, the variability of the dependent variable is shown due to the variability of the independent variable.
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![Master Regression and Feedforward Networks [2024]](https://traininghub.ir/image/course_pic/38375-x225.webp)
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Udemy
Henrik Johansson
Master Regression & Prediction with Pandas and Python [2024] 32:06:02
05/30/2024
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Udemy
EDUCBA Bridging the Gap
Logistic Regression & Supervised Machine Learning with R 3:50:49
01/01/2024
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Udemy
EDUCBA Bridging the Gap
Linear Regression & Supervised Learning with SPSS 3:09:27
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01/01/2024
Udemy
EDUCBA Bridging the Gap
Logistic Regression & Supervised Machine Learning with R 3:50:49
12/20/2023
Udemy
EDUCBA Bridging the Gap
Logistic Regression & Supervised Learning using SPSS 2:02:07
12/20/2023
