Build 2 linear regressions
Employer
[no-member:pro]Dina[/no-member:pro]
Project parameters
Type of cooperationOne-time project
SectionEducation and consulting
Prepaymentwithout prepayment
Payment methodsBank transfer, Electronic money
Acceptance of requestsfrom Jun 15, 2020 until Jun 22, 2020
Project description
It is necessary to build two linear regressions with conclusions, interpretation and results and graphics from the available data.
1. Data on the revenue of oil companies are available
It's a dependent variable. Independent variables are oil prices, export duties, investment in the industry, depreciation of fixed assets, etc. D. Regression is constructed, significant factors are identified, multicollinearity is excluded.
2. There are financial ratios of companies. The ratios of solvency and liquidity, for example. We build the dependence of these financial ratios on the significant factors that were identified in the first step. The goal is to forecast changes in financial ratios (for example, there is a forecast for the cost of oil in the near future).
1. Data on the revenue of oil companies are available
It's a dependent variable. Independent variables are oil prices, export duties, investment in the industry, depreciation of fixed assets, etc. D. Regression is constructed, significant factors are identified, multicollinearity is excluded.
2. There are financial ratios of companies. The ratios of solvency and liquidity, for example. We build the dependence of these financial ratios on the significant factors that were identified in the first step. The goal is to forecast changes in financial ratios (for example, there is a forecast for the cost of oil in the near future).
