【连载】CB Predictor操作手册(Crystal Ball Predictor 水晶球预测)

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Based on the results, you complete your memo to upper management. Current strategies seem to be working so you recommend funding another project instead.
在这个结果的基础上，你根据上级管理层的生成备忘录，你应该建议改变策略，投资其他的产品。


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以上是用CB Predictor进行一个简单的销售量的预测，明天会将CB Predictor如何进行工作的相关内容与大家分享

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How CB Predictor works CB Predictor如何工作？

Most historical or time-based data contain some kind of underlying trend or seasonal pattern. However, most historical data also contain random fluctuations — “noise”— that make it difficult to detect these trends and patterns without using a computer. CB Predictor uses sophisticated time-series methods to analyze the underlying structure of your data. It then projects the trends and patterns to predict future values.
大部分的历史或时间基础的数据都包含了相关的趋势和周期性，但是有些历史数据也是随机的，如果不借助电脑很难找到它的趋势性，CB Predictor使用时间序列趋势的图表方法对数据的结构进行分析，从而得到预测值的趋势和模型。

When you run CB Predictor, it tries each time-series method on your data and calculates a mathematical measure of goodness-of-fit. CB Predictor selects the method with the best goodness-of-fit as the method that will yield the most accurate forecast. CB Predictor performs this selection automatically for you, but you can also select individual methods manually or override the method CB Predictor recommends with a different one.
当你运行CB Predictor，它对历史数据运用各种时间序列的方法进行计算，得到一个最佳的数学度量。CB Predictor选择最佳的方法从而得到最精确的预测值，CB Predictor将为你自动选择最佳的方法，当然你可以根据自己的要求在方法图表中选择其他的。

The final forecast shows the most likely continuation of your data. Keep in mind that all these methods assume that some aspects of the historical trend or pattern will continue into the future. However, the farther out you forecast, the higher the likelihood that events will diverge from past behavior, and the less confident you can be of the results. To help you gauge the reliability of your forecast, CB Predictor provides a confidence interval indicating the degree of uncertainty around your forecast.
在你的数据上显示了最有可能的预测值，要记住，这些方法都是假定历史数据的趋势和结构将会延续到将来。但是，预测的值的时间越长，就会越有可能偏离以前的行为，预测的可信性也就越低。为了保证预测值的可靠性，CB Predictor提供了一个置信区间，通过这个置信区间来表示预测值的不可信度。

The final step of forecasting involves interpreting the results and integrating them into your decision-making process. CB Predictor provides comprehensive output to assist you in this process. You can request detailed reports, customizable Excel charts and graphs, and summary PivotTables. CB Predictor can also automatically create Crystal Ball assumptions for each forecasted value, letting you integrate risk analysis into the process.
在预测最后一步是解释结果，并将结果整合到您的决策过程中。文件提供全面的销售量预估，可以帮助您完成这一过程。您可以要求得出详细的报告，可定制的Excel图表和图表，数据透视表和汇总。CB Predictor还可以自动为每个水晶球预测值进行假设，帮你将入风险分析也考虑进来。


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Toledo Gas tutorial托莱多燃气公司案例

Suppose you work for Toledo Gas Company in the Residential Division. The Public Utilities Commission requires you to predict the gas usage for the coming year to make sure that the company can meet the demand.
假设你在托莱多住宅天然气公司工作，现在公共事业委员会要求你对明年的燃气使用量进行预测，以确保公司能够满足市民的需求。

To start the tutorial: 案例开始：

1.In Excel with Crystal Ball loaded, open the Toledo Gas spreadsheet, Toledo Gas.xls.
To find this example, select Help > Crystal Ball > Crystal Ball Examples and locate it in the list of CB Predictor examples, or browse to its folder. By default, the file is stored in this folder:
C:\Program Files\Decisioneering\Crystal Ball 7\Examples\CB Predictor Examples.
1、打开托莱多天然气电子表格，默认的存放位置是：C:\ProgramFiles\Decisioneering\Crystal Ball 7\Examples\CB Predictor Examples.

When you double-click the link or the file, the Toledo Gas spreadsheet appears in Excel.
双击文件夹后，托莱多燃气公司的数据表会打开


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2.Select cell C5.
2、选择单元格C5

3.Choose Run > CB Predictor.
The Input Data tab appears. CB Predictor’s Intelligent Input feature selects all the data from cell B4 to cell F100.
3、选择Run>CB Predictor
输入数据的表格出现，CB Predictor自动输入所有的数据，从B4：F100。


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4.Click Next.
The Data Attributes tab appears
4、点Next
出现数据分布对话框

5.Confirm that in Step 4, settings are “Data is in months with seasonality of 12 months.”

5、检查第四步，设置数据输入的周期性是12个月。

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Using regression使用回归
Through research, you know that your residential gas usage is primarily affected by three variables: new home starts, the temperature, and the price of natural gas. However, you aren’t sure how much effect each has on gas usage.
通过调查，可以知道住在天然气使用量是收到三个方面因素的影响：新房的数量、问题和天然气的价格。但是你不能确认天然气是使用效果是多大？

Because you have independent variables affecting a dependent variable (the variable that you are interested in), this forecast requires regression. For regression, CB Predictor uses a technique called HyperCasting™, which in one easy step:
因为对因变量影响的有多个自变量，预测的结果需要进行回归。用回归的方法，CB Predictor使用一种叫做HyperCasting的技术：

a. Creates an equation that defines the mathematical relationship between the independent variables and your dependent variable.
a、根据因变量和自变量之间的关系建立一个数学方程式。

b. Forecasts each independent variable using time-series forecasting methods.
b、使用时间序列预测方法预测每一个因变量

c. Uses the equation it created in the first step, combining the forecasted independent variable values, to create the forecast for the dependent variable.
c、使用第一步创建的方程式，结合自变量的预测值，生成因变量的预测值。

In the Toledo Gas spreadsheet, the dependent variable is the historical residential gas usage. The independent variables are:
•Number of occupancy permits issued (new housing completions)
•Average temperature per month
•Unit cost of natural gas
在托莱多天然气电子表格中，因变量是居民天然气使用量的数据，自变量是：
        允许使用的数量（新房的居住率）
        每个月的平均气温
        天然气的单位成本
To resume your tutorial:

6.Under Step 5, select Use Multiple Linear Regression.
6、在第五步之后，选择多元线性回归。
The Regression Variables dialog appears.
回归变量的对话框显示出来


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7.Confirm that Usage appears in the Dependent Variables list.
If it does not:
•Select Usage in the All Series list.
•Click >> next to the Dependent Variables list.
The Usage variable moves to the Dependent Variables list.
7、确认在因变量列表中有“使用量”这个因素
如果没有：在所有系列列表中选择“使用量”，点击chick移到因变量列表中。

8.Confirm that Occupancy Permits, Average Temperature, and Cost Of Nature Gas Per Ccf appear in the Independent Variables list.
If they do not:
•Select Occupancy Permits, Average Temperature, and Cost Of Natural Gas Per Ccf in the All Series list.
•Click >> next to the Independent Variables list.
The variables move to the Independent Variables list.
8、确认允许使用的数量（新房的居住率）、每个月的平均气温、天然气的单位成本是否在自变量列表中。
如果没有，选择自变量，移到自变量列表中。

9.Click OK.
The Data Attributes tab reappears.
9、点击OK。出现数据分布图对话框

10.Click Next.
The Method Gallery tab appears.
10、点解Next。出现概率分布图对话框。

11.Click Next again.
The Results tab appears.
11、点击Next。出现结果。

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Selecting results选择结果


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CB Predictor has five ways you can output your results:
CB Predictor 有五种结果输出的方法：

Paste Forecast 粘贴预测	Pastes the forecasted values to the end of your historical data. 将预测值粘贴到历史数据的最后面。
Charts 图表	Graphs historical, fitted, and forecasted data values, and a confidence interval. 将历史数据、历史最佳值、预测值和置信区间用图表表示出来。
Report 报告	Organizes and displays summary information, forecast values and a confidence interval, charts, and method information for any or all of your data series. 将数据的预测值、概要信息、置信区间、图表和方法形成报告。
Results Table 结果列表	Creates a table with all the forecasted values, fitted data, and a confidence interval. 将历史数据、历史最佳值、预测值和置信区间用结果列表表示出来。
Method Table 方法列表	Creates a table listing all the methods tried, the error values and statistics for each, and the parameters for each. 将所有的方法的误差值、统计值和参数用表格列出来。

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Paste Forecast and Charts are the most common results. The other settings provide more detailed output that includes information you might use for presentations or to investigate various forecasting methods.
粘贴预测和图表预测是最通常的表示结果，其他的方法提供详细的输出结果，包括你可以使用的用来预测和报告的各种方法。

This tutorial produces more detailed output. To continue with the tutorial:
这个案例会得出许多详细的结果。
12.Under Step 7, forecast the monthly usage for the next year by entering 12 in the field.
12、在第七步的基础上，在表格中输入需要预测的明年12个月的天然气使用量。

13.Select the Paste, Report, and Methods Table result settings.
13、选择粘贴、报告和方法列表的输出结果。

14.In the Title field, type “Toledo Gas Usage Forecast.”
Now, the dialog looks like Figure 1.13 on page 21
.14、输入标题。

15.Click Preferences
15.点击参数

The Preferences dialog appears as shown in Figure 1.14.
图1.14显示了参数设定对话框


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Notice that Paste Forecasts... is checked. This prepares forecasted independent variable data for use as assumptions in Crystal Ball risk analysis simulations.
注意粘贴预测中，因变量预测的数据是为了之后用水晶球进行分析，形成模型。

16.Select the Report tab.
16、选择报告
The Report preferences appear.
结果参数表会显示出来：

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17.Under Methods, select Three Best from the list and unselect the Parms (Parameters) setting.
This removes the method parameters from the report.
17、在方法列表中，选择三个最好的列表，不要选择设置参数。

18.Click OK.
The Results tab reappears.
18、点击ok。结果显示出来

19.Click Preview.
The Preview Forecast dialog appears.
19、点击Preview。预测结果预览对话框显示出来。

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Previewing results对结果进行预览

Before you output results to your spreadsheet, you can preview the forecasted values and the best method selected with the Preview Forecast dialog.
在将结果输出在电子表各前，可以对预测值和最佳方法在Preview Forecast对话框中进行评估。

In the Preview Forecast dialog, you can preview the forecasted values for all the data series and all the methods run for each. After viewing the forecast values for each method, you can also override the selected method to use for the final forecasted values.
在Preview Forecast对话框中，你可以对所有方法和数据得出的预测值进行评估，在查看不同方法得到预测值后，可以得到最后的预测值。

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To continue with your tutorial:继续会案例进行操作：

20.Select Average Temperature from the Series list in the upper left corner of the Preview Forecast dialog.
20、选择平均温度查看预测值情况

Forecasted values appear for Average Temperature. Seasonal Additive is identified as the best-fitting method as in Figure 1.17.
在图1.17中选择最适合的预测方法后，平均气温的预测值显示出来

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