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Student
Title
Supervisor
Faculty
Educational Programme
Final Grade
Year of Graduation
Natalia Volkova
The System for Assessing the Profitability of Expanding the Network of Household Stores
Business Informatics
(Bachelor’s programme)
2016
In this graduation work dependence of Moscow do-it-yourself stores revenue on various factors is analyzed.

This research objective is development of regression model illustrating the dependence of household goods shop revenue from the territorial, seasonal factors and factors connected with the shop size.

As a dependent variable the monthly revenue has been taken. As independent factors have been taken:

‒ identifier of shop;

‒ the administrative district;

‒ year (for estimating the financial results during the period in 3 years);

‒ month (for identification of seasonal factor existence);

‒ average population density in new buildings which are at distance less than 2 km from particular store.

For the main aim achievement the following tasks have been formulated:

‒ collecting the original data characterizing do-it-yourself stores money turnover;

‒ the data preparation for the regression model development including removal of emissions, elimination of data incompleteness, rationing of indicators values;

‒ development of regression model on the basis of statistical methods;

‒ presenting the results in a graphical format, and also in the form of the text report.

Research was conducted with use of methods of probability theory and mathematical statistics, databases data modeling (MS SQL Server), and also with use of the specialized RStudio development environment.

The received model demonstrates that the revenue positively depends on average population density in nearby new buildings. The territorial factor is also statistically significant: there are certain administrative districts which are more preferable for do-it-yourself shops opening. The results received for a time factors are logical and reflect crisis impact on sales volumes, and also preferences in the choice of month for flat renovation.

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