What things can i do with set of X and Y variables

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SUMMARY

The discussion centers on enhancing a project involving a set of X and Y variables, where linear and polynomial regression have already been implemented. Participants suggest additional analyses such as calculating squared errors, correlation coefficients, and F-scores for regression coefficients. Logistic regression is recommended as a more complex alternative, while normal quantile plots are proposed for visualizing regression errors. The user seeks straightforward implementations to add detail without significant complexity.

PREREQUISITES
  • Understanding of linear regression and polynomial regression techniques
  • Familiarity with Java programming language
  • Knowledge of statistical concepts such as correlation and F-scores
  • Basic understanding of logistic regression and quantile plots
NEXT STEPS
  • Implement logistic regression using Java libraries
  • Calculate and visualize squared errors and correlation coefficients
  • Create normal quantile plots for regression error analysis
  • Explore additional statistical distributions applicable to X and Y datasets
USEFUL FOR

Data analysts, students in statistics or data science, and Java developers looking to enhance their projects with statistical analysis techniques.

pablo26
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Hi i am currently doing a project and I am taking as input a set of X and Y variables.
I have implemented linear regression and polynomial regression (i have a panel of functions)..so i was wondering if anybody could suggest maybe one or two other things i could implement with the x and y data sets that can be done in java and is not too complicated as i have to submit it soon. thanks in advance
 
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A note on terminology: you mean you have one variable X, and one variable Y, and a number of values for those variables.

What you might do depends on what your assignment is looking for. Do you compute squared errors/correlation, or F-scores for your regression coefficients? Those are useful. If you want to do entirely different kinds of regression you might try implementing logistic regression (although that might be a little trickier since it is not closed form and must be computed numerically). A normal quantile plot for your regression error is another thing you could do.
 
Hi well this isn't an assignment but a project that i get to choose what goes but as i am running short on time i don't want anything to heavy. Just some things to make it look more detailed the normal quartile plots is one and i was wondering if there are any distributions that are not too much work that might apply... thanks for your help.
 

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