The information of the weight table ( weight and variance estimates) can be visualized in a weight plot.
The following plot shows the results from a linear regression model of predicting the number of rented bikes on a particular day, given weather and calendar information. Choose all correct interpretation/explanations.

Question

The information of the weight table ( weight   and  variance  estimates) can be visualized in a weight plot.
The following plot shows the results from a  linear regression  model of predicting  the  number of rented bikes   on a particular day, given weather and calendar information. Choose all correct interpretation/explanations.

Answer

seasonSPRING has a strong positive weight on the prediction, and could be an important feature.

Answer

For any models, the important features are always the same.

Answer

Some confidence intervals are very short and the estimates are close to 
zero (e.g., temp), yet the feature effects could be statistically significant, if the features are measured on different scales.

Answer

weathersitRAIN/SNOW/STORM has a strong negative weight on the prediction, so that it could not be an important feature.

Crowdly

The information of the weight table ( weight and variance estimates) can be ...

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