Содержание
- 2. 2 directions in demand assessment statistical analysis market intelligence Задача статистического анализа: определение параметров функции спроса
- 3. Statistical analysis Steps: 1) Collection, validation and assessment of data 2) The choice of the information
- 4. 1) Collection, validation and assessment of data time series cross-sectional data Statistical analysis
- 5. time series 1) Collection, validation and assessment of data Statistical analysis Examine time changes in the
- 6. Adjustment of necessary information in order to avoid effects such as inflation Deflationary correction: divide all
- 7. Statistical analysis 1) Collection, validation and assessment of data cross-sectional data Considered changing the variables from
- 8. Ex: In order to determine the effect of prices on demand, as a variable can be
- 9. Statistical analysis 2) The choice of the information curve The results of the observations are used
- 10. When choosing a curve there are two main questions: What type of equation it is necessary
- 11. If the trend of the experimental values of the dependent variable is approximately linear, and there
- 12. If the data can be reduced to a single independent variable (e.g. price) and the trend
- 13. If the trend of the dependent variable is nonlinear and the function has a single independent
- 14. simple linear regression STEP 1. Data collection TASK: TO FIND THE REGRESSION FUNCTION for THESE DATA!
- 15. STEP 2. Organization variables in time simple linear regression Причины: визуализация; определение линейности или нелинейности для
- 16. simple linear regression STEP 3. Organization of a scatter plot Database for simple linear regression is
- 17. simple linear regression STEP 4. Evaluation of the regression line When making the regression analysis we
- 18. simple linear regression STEP 4. Evaluation of the regression line Period Observa-tion X Observa-tion X Observa-tion
- 19. simple linear regression STEP 5. Comparison of calculated and actual values How well our estimated regression
- 20. simple linear regression Interpretation of parameters The "a" parameter determines the point of intersection of the
- 21. simple linear regression Evaluation of the regression equation How informative or accurate the determined Y is?
- 22. The root – mean - square error of the estimation, Se; Represents the deviation of experimental
- 23. The root - mean - square error of the estimation, Se; ˄ Root-mean-square error Observed Y
- 24. The more root-mean-square error is, the greater the range of deviations are Root-mean-square error, Se; If
- 25. coefficient of determination, r^2 Shows how well the regression model describes the variation of the dependent
- 26. the correlation coefficient, r, Determines the degree of connection between variables -1 1
- 28. Скачать презентацию