2. Select the data set “Energy efficiency” from UCI machine learning repository (https://archive.ics.uci.edu/ml/datasets.php), do linear regression analysis in terms of the data, and answer the following questions or requirements:
2.1 Fit two multiple regression models to predict heating load and cooling load, respectively, using all the 8 predictors, write up the linear expressions and explain the coefficients in the models.
2.2 Which of the predictors can you reject the null hypothesis?
2.3 On the basis of your response to the previous question, fit a smaller model that only uses the predictors for which there is evidence of association with the outcome.
2.4 How well do the models in (2.1) and (2.3) fit the data?
2.5 Is there evidence of outliers or high leverage observations in the model from (2.3)?
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