Tula, Tula, Russian Federation
The article contains an attempt to expand the list of indicators for a discriminant model designed to predict the level of innovative development of regions. Data from the regions of the Central Federal District became the basis for selecting factors and building a model. This time, indicators were chosen that characterize activities that logically precede innovation, namely, research and development. As a result, calculations yielded coefficients for the model and the numerical value of the criterion for assessing the level of innovative development of regions.
innovative development, scientific research and development, rating of regions, coefficient matrix, discriminant model
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