Data Analytics- R (programming)

Questions/Hypotheses

Write one or multiple questions or hypotheses you want to explore with the data sets. After each question, state your expected answers, which may be different from your data analysis because you have not yet analyzed the data. 

The increasing concern on climate change has forced the car manufacturers to shift their product lines or modify their existing products specifications In the collected data set that contains engine information and gas consumption. With everything else being equal, carbon dioxide emitted from a driving vehicle usually depends on fuel type, fuel economy, and numbers of mille drived. We hypothesize that the selected 6 variables that are Engine Size, Cylinders, Fuel Type, Consumption City, Consumption Hwy, and Consumption Comb can be used as predictors to estimate the carbon dioxide emission and would like to find out how significant of each variable to a car’s associated carbon dioxide emission.  We expect that the 6 variables are all relevant to the car carbon dioxide emission and most significant variables are expected to be fuel type and fuel consumption combo.

Methodologies

Write a complete, clear description of the analysis you performed. This should be sufficient for someone else to write an R program to reproduce your results. It should also likely be helpful to people who read your code later. This section should tie your computations to your questions/hypotheses, indicating exactly what results would lead you to what conclusion. You may want to provide the key statistics, e.g., t-statistic, z-statistic, p-value s, R2 and the adjusted R2, etc.

Results and Conclusion. 

Discuss your results. Focus in particular on the results that are most interesting, surprising, or important. Discuss the consequences or implications. Interpret the results: if the answers are unexpected, then see whether you can find an explanation for them, such as an external factor that your analysis did not account for. You may also want to make predictions for new scenarios.

Appendix

Put plots, tables, technical details or other results in the appendix if necessary. This part is optional.