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Linear_Regression_Tutorial👨🏼‍🏫

The goal of this repository is to explains the assumptions of linear regression in detail. These steps can be applied on other problems to be able to make better decisions about which model to use.

✏️About Dataset.

The data used in this study were obtained from the database of Eurostat, which is the statistical office that collects data for the European Union. The analyzed data includes the following European countries (27 countries): Belgium, Bulgaria, Czech Republic, Denmark, Germany, Estonia, Ireland, Greece, Spain, France, Croatia, Italy, Cyprus, Latvia, Lithuania, Luxembourg, Hungary, Malta, Netherlands, Austria, Poland, Portugal, Romania, Slovenia, Slovakia, Finland and Sweden. We note that the study proposes a more varied approach, taking into account different type of countries (developed and under developed), the observed period being from 2011 to 2021.This aspect leads to a large variety of values for the considered variables.

✏️The macroeconomic indicators analysed in this study are:

  • PEC (Primary energy consumption)

  • FEC (Final energy consumption).

We are interested in understanding the relationship between the variables involved in the study in order to have a broader view of the described economic context.

✏️Data.

The values of the macroeconomic indicators for each country were obtained as the arithmetic mean of the values of these variables in the interval 2011-2021 and were previously processed from the files FEC.xls and PEC.xls. We propose to validate/invalidate the following hypothesis using the linear regression technique.

Hypothesis: Influence of PEC on FEC.

The correlation based on hypothesis aims to determine the impact that “Final energy consumption” has on “Primary energy consumption”.

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