Nayak S Supervised Machine Learning Linear Regression 2022

Learn regression analysis at a deeper level with guidance written in everyday language!

Intuitively understand regression analysis by focusing on concepts and graphs rather than equations. Learn practical tips for modeling your data and interpreting the results. Feel confident that you're analyzing your data properly and able to trust your results. Know that you can detect and correct problems that arise.

Progress from a beginner to a skilled practitioner ready for real-world applications!

After an overview of how regression works and why to use it, the book covers a range of topics, including specifying and assessing models, practical applications, types of effects, statistical significance, predictions, and an array of problem-solving techniques. Contains practical and analytical guidance.

[*] Select the correct type of regression analysis.
[*] Specify the best model and assess how well it fits the data.
[*] Interpret the results.
[*] Understand main effects, interaction effects, and modeling curvature.
[*] Use polynomials, data transformations, and weighted least squares.
[*] Generate predictions and evaluate their precision.
[*] Check the assumptions and resolve issues.
[*] Identify and manage unusual observations.
[*] Examples of many regression models and scenarios.
[*] Access free downloadable datasets so you can work the examples yourself.

https://rapidgator.net/file/a03b250b6270e36b0ba8287962983a96/

https://nitroflare.com/view/ACBA3811A364AE3/