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研究方向，Science, International Management

master level

在实际操作中，assessment会涉及到许多现实应用的案例，比如

探究rating和inflation的关系；

时序分析time series analysis；

销售额的预测；

ACF test预测；

学生需要学会选择适合的模型进行预测。

1 Introduction
1.1 Modelling: Definition, motivation & examples
1.2 Decision support models
1.3 Optimization problems
2 Operation research代写
2.1 Basics & Optimization problem types
2.2. Linear optimization
2.2.1 Graphical solution
2.2.2 Simplex method (Excel solver)代写
2.2.3 Potential problems
2.3 Discrete Optimization
2.4 代写Decision making under certainty, uncertainty & risk

3 Forecasting
3.1 Introduction
3.2 Basic steps
3.3 Exploratory analysis: Graphical analysis & descriptive statistics代写
3.4 Measures of forecast accuracy
3.5 时间序列分析代写Time series transformations
3.5 Time series decomposition
3.6 Exponential smoothing
3.7 Linear regression
3.8 Box-Jenkins method & AR(I)MA models代写
4 Outlook
4.1 Further Forecast methods
4.2 AI
4.3 Model Risk

Linear optimization – Excel Solver代写

Step #1: Data Cells
Enter all of the data for the problem on the spreadsheet.
Make consistent use of rows and columns.
t is a good idea to color code these “data cells” (e.g., light blue).

Step #2: Changing Cells
Add a cell in the spreadsheet for every decision that needs to be made.
If you don’t have any particular initial values, just enter 0 in each.
It is a good idea to color code these “changing cells” (e.g., yellow with border).

Step #3: Target Cell
Develop an equation that defines the objective of the model.
Typically this equation involves the data cells and the changing cells in order to determine a quantity of interest (e.g., total profit or total cost).
It is a good idea to color code this cell (e.g., orange with heavy border).