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Применение компьютерных технологий в математических и экономических расчётах

1.

Применение компьютерных
технологий в математических и
экономических расчётах

2.

Note on Generated Content
This slide deck has been generated by an AI. The system may occasionally
generate incorrect or misleading information and produce offensive or biased
content. It is not intended to give advice.

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Applications of Information Technology in Economics
● Data Analysis: Using statistical software to analyze large datasets
● Financial Modeling: Creating models to forecast financial performance
● Forecasting: Using historical data to predict future trends

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Areas of Information Technology in Economics
● Databases: Storing and managing large amounts of data
● Spreadsheets: Organizing and analyzing data using formulas and functions
● Statistical Software: Analyzing data using statistical methods

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Prospective Directions for Excel in Calculations
● Financial Modeling: Creating models to forecast financial performance
● Budgeting: Creating and managing budgets for businesses and organizations
● Forecasting: Using historical data to predict future trends

6.

Using Excel in Economic and Mathematical
Calculations
● Formulas: Using built-in formulas to perform calculations
● Functions: Using built-in functions to perform more complex calculations
● Data Analysis: Using Excel's data analysis tools to analyze data

7.

Solving Dynamic Programming Problems (Robot)
● Dynamic Programming: A method for solving complex optimization problems
● Excel Solver: A tool for solving optimization problems in Excel
● Example Problem: Solving a robot navigation problem using dynamic
programming and Excel Solver

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Solving Optimization Problems
● Linear Programming: A method for optimizing linear functions subject to
constraints
● Nonlinear Programming: A method for optimizing nonlinear functions subject
to constraints
● Excel Solver: A tool for solving optimization problems in Excel

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Types of Mathematical Models
● Linear Models: Models that assume a linear relationship between variables
● Nonlinear Models: Models that assume a nonlinear relationship between
variables
● Stochastic Models: Models that incorporate randomness and uncertainty

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Solving Optimization Problems
● Linear Programming: A method for optimizing linear functions subject to
constraints
● Nonlinear Programming: A method for optimizing nonlinear functions subject
to constraints
● Excel Solver: A tool for solving optimization problems in Excel

11.

Applications of Mathematical Models
Forecasting: Using models to predict
future trends and outcomes
Decision-Making: Using models to make
informed decisions
Risk Analysis: Using models to assess and
manage risk

12.

Case Studies
● Case Study 1: Using Excel to optimize a supply chain
● Case Study 2: Using mathematical models to forecast demand for a new
product
● Case Study 3: Using dynamic programming to optimize a production process

13.

Conclusion
● The use of computer technology in mathematical and economic calculations
has many benefits, including increased efficiency and accuracy.
● Excel is a powerful tool for calculations in economics, with many potential
applications in financial modeling, budgeting, and forecasting.
● Dynamic programming and optimization methods can be used to solve
complex problems and optimize functions subject to constraints.
● Mathematical models have many applications in economics, including
forecasting, decision-making, and risk analysis.
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