# r studio

**Question description**

Once again check out wine quality data set described in the web page below: http://archive.ics.uci.edu/ml/machine-learning-databases/winequality/ winequality.names Remember the Red Wine data set (winequality-red.csv) contains 1599 observations of 11 attributes. The median score of the wine tasters is given in the last column. Note also that the delimiter used in this file is a semi colon and not a comma. This problem is to create an ordinary least squares linear model (use the lm function in R) for this data set using the first 1400 observations. Don’t forget to scale each column before you create the model. Next check the model’s performance on the last 199 observations. How well did the model predict the results for the last 199 observations? What measure did you use to evaluate how well the model did this prediction? Next use the model to predict the results for the whole data set and measure how well your model worked

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