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Statistics for Data Science
book

Statistics for Data Science

by James C. Mott, Rajprasath Subramanian, Shaikh Salamatullah, James D. Miller, Vijayakumar Ramdoss
November 2017
Beginner
286 pages
8h 13m
English
Packt Publishing
Content preview from Statistics for Data Science

Does it fit?

After selecting a model that you feel is appropriate for use with your data (also known as determining that the approach is the best fit), you need to validate your selection, that is, determine its fit.

A well-fitting regression model results in predicted values close to the observed data values.

The mean model (which uses the mean for every predicted value) would generally be used if there were no informative predictor variables. The fit of a proposed regression model should, therefore, be better than the fit of the mean model.

As a data scientist, you will need to scrutinize the coefficients of determination, measure the standard error of estimate, analyze the significance of regression parameters and confidence intervals ...

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Publisher Resources

ISBN: 9781788290678