Economic Applications in MS Office (in English)

Syllabus

Thematic definition of lectures: 1. Use of MS Excel in business analysis. Source files for data analysis in MS Excel from different areas of business management. Role, importance of constructing output reports using filters, contingency tables, subtotals. Use of matrix formulas - algorithm of writing and calculation. 2. Financial functions. Types of financial functions, construction of formulas and arguments of functions in the calculation of trade margin, mark-up, rebate and critical point of production. Application of selected financial functions in MS Excel in the calculation of financial resources of the enterprise. Notation, arguments and limitations of functions aimed at calculating the financial resources of an enterprise, principal repayment, interest, loan, interest rate, present value of investment, future value of deposit, number of periods, accumulated interest and principal amount. Functions calculating interest rates and annuities. 3. Investment projects. Application of selected financial functions in MS Excel in the calculation of investments, cash flow analysis, methods of evaluation of investment projects. Construction of formulas, notation of arguments of financial functions focused on investment projects and their limitations. 4. Depreciation. Arguments, notation and limitations of financial functions aimed at calculating accounting depreciation and tax depreciation. 5. Descriptive statistics. Statistical functions in MS Excel, construction of formulas and arguments of functions. Descriptive statistics using an analytical tool in MS Excel. Position indicators and their interrelationships. Standardization of values and its meaning. Frequency analysis, histogram. Interpretation of results of statistical functions. Normality of data distribution, Gaussian curve. Hypotheses and their verification, statistical significance, population and selection, accuracy of measurement and errors in measurement, validity, objectivity, reliability. 6. Comparing groups. Statistical functions focused on group comparisons. Comparison of groups using parametric tests to the mean value. Explanation of normality as conditions for the use of parametric tests and data normality tests. Comparison of two independent groups. Comparing three or more groups. Calculation of the size of the difference between groups (effect size) and their meaning and practical interpretation. 7. Measuring relationships between variables using statistical functions. Statistical functions and analytical tool used to measure relationships between variables. Graphical representation of the dependency. Numerical measurement of the relationship between variables using correlation and simple regression. Interpretation of the values of the calculated correlation coefficient, calculation of the coefficient of determination, interpretation and recording of results. Explanation of assumptions of regression analysis, dependent and independent variable. Regression model for simple regression analysis. 8. Statistical functions and their application and interpretation in final theses. Basic concepts related to research, research, scientific research, procedure and determination of research questions, procedure and determination of assumptions. Description of variables and their types, compilation of the questionnaire, description of frequent errors and practical advice on data collection in the form of a questionnaire. 9. MS Excel add-ins and extensions. Activation of MS Excel add-ins and extensions. Creation and arguments of MS Excel add-ins and extensions - scenarios, solution search, data table, solver. Demonstration of the use of MS Excel add-ins in managerial decision making. 10. MS Office 365. MS Office 365 cloud-based office suite. Comparison of MS Office (desktop) vs. MS Office 365. Open-source alternatives. MS Office 365 platforms across installations, groups and categories with links to enterprise use. 11. Macros. Principle of work, algorithm of macro writing and possibilities of writing in MS Word text editor, MS Excel spreadsheet and MS Access database application program. Demonstration of demonstration of work without and with the use of macros. Possibilities of editing the created macro and its execution. Information security, macro security, macro viruses and infiltration protection tools. 12. Big Data. Importance of data in the knowledge society, knowledge pyramid, types of data in terms of their structure. Features of Big Data, technology platforms for Big Data processing. Benefits of Big Data technology for the enterprise. Current state of Big Data in Slovakia. 13. Database processing. Transactional and multidimensional databases. Basic data models. SQL language, its meaning, basic syntactic constructions, examples of practical use on specific databases. Data Mining - objectives, architecture of a typical IS for DM, data types suitable for DM. Knowledge acquired by mining. DM process. Mining relationship types, examples of mining tasks. DM as part of machine learning. Thematic definition of exercises: 1. Analytical outputs and output reports. Creation of analytical outputs using MS Excel functions and tools - mathematical, search, logical functions, filters, subtotals, matrix formulas. Creation of single-result array formula and multi-result array formula. Working with extensive data tables. 2. Financial functions. Application of financial functions in MS Excel in solving examples with economic issues. Application of financial functions in calculating examples focusing on - interest rates and annuities, amortization schedule, cash flow analysis, calculation of rate of return. Functions calculating interest rates and annuities. Algorithm of financial functions, possibilities of their application, characteristics, principles and limitations of individual arguments of financial functions. Economic evaluation and formulation of conclusions from the results of financial functions. 3. Investment projects. Application of selected financial functions in MS Excel in the calculation of examples with economic topics focused on investments, cash flow analysis, methods of evaluation of investment projects. Pointing out the construction of formulas, writing the arguments of these financial functions and their limitations. 4. Depreciation. Financial functions aimed at calculating depreciation. The use of financial functions in solving examples aimed at calculating accounting depreciation and tax depreciation. Solving examples focused on the problem of calculating accounting depreciation and tax depreciation in MS Excel. 5. Descriptive statistical functions in MS Excel. Descriptive statistical functions in MS Excel and their importance in data analysis, calculations, output reports. Central tendency indicators, variability and interrelationships between them. Use of the analysis tool in MS Excel to calculate statistical functions. Interpretation of the results of statistical functions. 6. Comparison of groups in MS Excel (statistical functions). Use of an analytical tool in MS Excel to compare two or more independent groups. Calculations of the size of the difference between groups and their significance, practical interpretation and recording of results. 7. Analysis of interdependence of variables using statistical functions in MS Excel. Creating graphs to graphically display the dependency. Using functions and an analytical tool to numerically measure the relationship between variables. Correlation calculation. Interpretation of the height of the values of the correlation coefficient and practical recording of the results of statistical functions. 8. Analysis of hypotheses, Goal Seek. Overview of MS Excel tools for hypothesis analysis. Goal Seek - principle of use, notation and arguments. Obtaining the desired result by fitting one input value, backward solution. Application of the Goal Seek tool to analyse labour productivity by changing costs, revenues and number of workers, to analyse the level of the creditworthiness index when changing individual input indicators. 9. Data table. Analyzing data by using the Data Table tool, writing arguments when one or two variables change. Solving problems using the Data Table to make decisions about solving specific economic problems. 10. Scenario Manager. Defining different values of input data, obtaining relevant results and then performing hypothesis analysis by switching scenarios or creating a summary or contingency table of scenarios. Solving specific economic problems using the Scenario Manager tool. 11. Solver. Applying the Solver tool to solve optimization problems, setting the target cell, defining the group of changed cells, defining the assumptions and constraints of the changed cells. Solving specific optimization problems using the Solver tool. 12. SQL queries in MS Access. Queries in MS Access and their meaning. Characteristics of the SQL language, basic groups of SQL statements, syntax of selected SQL statements, creation of selection criteria, syntax of aggregation functions, joining tables, ordering data, grouping data. Query creation in SQL, comparison of possible ways of query creation in MS Access. Solving queries on the example of a specific database. 13. SQL subqueries in MS Access. Subqueries as one type of queries specific to the use of the SQL language in MS ACCESS. Group of subqueries with SQL statement in Criteria cell, group with SQL statement in Field cell. Subqueries for searching the values of the main query, multiple nested subqueries. Other specific queries: union query, commit query, data defining query, SQL query in Visual Basic for Applications (VBA) programming code.