This data set includes the environmental variables ozone, humidity, and temperature, along with day of the week and day of the year. Ozone has some level of a relationship with human disturbances, especially actions which alter temperature, such as vehicle use and and greenhouse gas outputs. This report will attempt to predict the daily ozone level, our response, with a multiple regression Bayesian framework. A smoothing spline will be implemented to help make predictions and identify patterns in the data set.
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This report will attempt to predict the daily ozone level, our response, with a multiple regression Bayesian framework. A smoothing spline will be implemented to help make predictions and identify patterns in the data set.
Cimm-Yeoman/Daily-Ozone
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This report will attempt to predict the daily ozone level, our response, with a multiple regression Bayesian framework. A smoothing spline will be implemented to help make predictions and identify patterns in the data set.
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