1. Pick any dataset relevant to your major that you would like to analyze. Avoid use the same or similar datasets to one you use for your final project or previous assignments. Make sure not to use datasets from an educational literature on regression analys.
2. Identify an output variable and a set of at least five input variables to test.
3. Use R, Python or other tool to compute regression model. This process should include selection of appropriate input variables (there should be at least two left, otherwise use another dataset).
4. Submit a Word report describing each step and a result of this process, include relevant scripts and outputs produced by the tool you use. Your report has to include:
   1. Description of the dataset.
   2. Explanation what is the real-world application of the ability to predict the chosen output variable.
   3. Description of the regression model and its results.
   4. Demonstrate how the model can be used to predict the output variable (use few examples from the dataset, plot the predicted value and the actual value). Discuss the model's accuracy.
   5. Explain the underlying nature of the computed regression model.