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

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Methods table方法图表

Only one setting in the Results tab affects the Methods table: the Methods Table setting, which selects whether to generate it.
只有一个结果图表设置会影响的方法表：方法表的设置，选择是否生成它。

If you select Methods Table and click Run, CB Predictor generates one Methods table for your entire forecast. The Methods table appears either on a different worksheet or on a different workbook, depending on the selected settings in the Methods Table Preferences dialog.
如果选择方法图表，CB Predictor会对预测值生成一个方法图，方法图表会在另外的sheet表或者新的excel工作表中生成，这可以在方法图表属性对话框中进行选择。

The Methods table reports all the parameters and statistics for one or all the methods you selected in the Method Gallery. In the table, the methods appear in the order from the Method Gallery. The method used to generate the forecasted values, either the best method or the overriding method, is highlighted in bold, blue text. The method is likely to be different for each forecasted series.
方法图表报告中会生成一个或所有的方法的参数和统计方法。在图表中，按一定的顺序排列。也会生成最佳方法和覆盖方法的预测值，用高亮蓝色来标明。，

To compare the quality of the results of different time-series forecasting methods, check the errors: RMSE, MAD, and MAPE. For all of these, the smaller the better. So, you can compare the RMSE of one method to the RMSE of another method, and the smaller one should be ranked better. However, you cannot compare the RMSE of one method to the MAD or MAPE of another method. For more information, see “Time-series forecasting error measures”
为了比较不同时间序列预测的方法，可以检查它们的误差：RMSE,MAD和MAPE.误差越小的越好。所以你可以比较一种方法的RMSE和另一种方法的RMSE，误差越小的排在前面。但是不能以一种方法的RMSE和另一种方法的MAD或者MAPE进行比较。

To compare the quality of a regression, look for the following values:
对回归的比较，可以查看以下数值：

Table 3.3 Evaluating regression quality回归质量评价

Statistic 统计	Range 排列	Ideal value 关键值	Shows that: 含义
R2 or Adjusted R2 R2或调整 R2	0 to 1 0 到 1	Close to 1 趋向1	The linear regression accounts for almost all the variability in the dependent data. 线性回归方程中所有的自变量都是可用的
F probability F值	0 to 1 0 到 1	Less than 0.05 小于0.05	The quality of the overall regression (dependency of the dependent variable on the independent variables) is good. 整体回归质量（对因变量的自变量的依赖）是好的
t probability t 值	0 to 1 0 到 1	Less than 0.05 小于0.05	The quality of the coefficient of the regression equation is good. 回归方程中回归系数的质量是好的
Durbin-Watson Durbin-Watson值	0 to 4 0 到 4	2 2	No auto-correlation （ at lag 1) exists 不存在自相关
Theil’s U 泰尔U值	Greater than 0 小于0	Less than 1 小于 1	The quality of the results is better than guessing. 结果的质量比猜测的好

For more information on these statistics, see “Regression statistics”
更多的信息，可以查看“回归统计”


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Customizing reports and charts定制报告和图表

You can customize reports and charts by customizing the Excel templates that control how they look. The CB Predictor folder contains these two template files: Report and Charts.

To customize reports or charts:

您可以自定义报告，并通过自定义的Excel图表模板来进行设定。CB Predictor文件夹中包含这两个模板文件：报告和图表。

要自定义报告或图表：

1.In the CB Predictor folder, open the appropriate template file.

1、在CB Predictor文件夹中，打开模板文件

2.Make any style changes you want.

For example, in the report, you can change the font of the title, the width of the columns, or turn on grid lines. For the chart, you can change the chart type or the color of the upper confidence interval and fitted lines, change the background color, or change the angle of the horizontal axis labels.

2、设定需要的格式

例如，在报告中，您可以更改标题的字体，栏，或打开网格线的宽度。对于图表，您可以更改图表类型或置信区间的上线，并配备颜色，改变背景颜色，或更改标签的水平轴角。

3.Save and close the template file.

The next time CB Predictor generates a report or chart, it uses the modified template and appears with the new style.

3、
保存和关闭文件夹

保存或关闭文件夹后，再打开CB Predictor文件的时候，会生成新的模板。

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明天开始第四章{:8_306:}

漂在生活

{:8_307:}waiting for u

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Chapter 4              
Examples案例
In this chapter在本章中
•Overview
•Inventory control
•Company finances
•Human resources
•概述
•库存控制
•公司财务
•人力资源

This chapter describes a detailed Excel model for Monica’s Bakery. The workbook has worksheets for sales data, operations, and cash flow. The Sales Data worksheet contains all the historical sales data that is available for forecasting. The Operations worksheet calculates the amount of different ingredients required to make different quantities of the three different breads. The Cash Flow worksheet calculates how much money the bakery has to spend on various capital projects. The Labor Costs worksheet estimates the increase in hourly wages to decide whether to invest in labor-saving equipment.
本章描述了莫尼卡的面包房详细Excel模型。该工作表包括销售数据，材料和现金流量表。销售数据表中包含所有的历史销售数据，用于预测可用。材料工作表计算所需的利用三种不同的材料不同数量的不同成分含量。现金流量表计算出多少钱，面包房已动用各种资本项目。对劳动力成本估计，每小时工资增加，以决定是否投资于节省劳力的设备。

Examples show to use this type of information to appropriately stock bread ingredients, plan for major purchases such as constructing a silo or buying a delivery van, and estimate the value of the business.
案例表明面包原料的存储量，计划和主要开支比如油，或者是否需要购买一辆汽车，从而来制定采购计划，确定企业的价值。

Overview概述

Monica’s Bakery is a rapidly growing bakery in Albuquerque, New Mexico. It opened in March of 2000, and Monica has kept careful records (in an Excel workbook) of the sales of her three main products: French bread, Italian bread, and pizza. With these records, she can better predict her sales, control her inventory, market her products, and make strategic, long-term decisions. To see Monica’s workbook, in the CB Predictor Examples folder, open Bakery.xls. By default, the file is stored in this folder: C:\Program Files\Decisioneering\Crystal Ball 7\Examples\CB Predictor Examples.
These numbers are ready to forecast. The following examples track Monica's decision-making processes as she works through both short-term and long-term decisions.
莫尼卡的面包是在新墨西哥州阿尔伯克基迅速增长的面包店。它设立于2000年3月，莫妮卡一直仔细记录（在Excel工作簿）她的三个主要产品的销售：法国面包，意大利面包，和比萨饼。有了这些记录，她可以更好地预测她的销售，库存控制她，她的产品市场，并作出战略性，长远的决策。要查看在CB预估的例子文件夹莫尼卡的工作簿，打开Bakery.xls。默认情况下，该文件存储在此文件夹：C:\Program Files\Decisioneering\Crystal Ball 7\Examples\CB Predictor Examples。
    这些数字已经准备好预测。下面的例子是莫尼卡的决策过程，她通过短期数据来做出短期和长期的决定。


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Inventory control库存控制

The initial reason that Monica needs to forecast is to maintain enough ingredients to keep up with her production. Monica's Bakery places regular orders for ingredients, and Monica’s distributors give her discounts for buying in bulk. However, she must balance this savings with the freshness of her products, which requires using the freshest ingredients possible.
莫妮卡需要预测的最初原因是要保持足够的原料，以配合她生产。莫尼卡的面包成分定期订单，和莱温斯基的分销商给予她在大量购买的折扣。不过，她必须保持库存和产品的平衡，这就必须使用最新鲜的配料库存。

In the past Monica scheduled deliveries to her business of bagged flour and other ingredients whenever “it looked low.” Sometimes this required paying for express delivery when demand was high or, when the demand after placing the order was unexpectedly low, letting ingredients sit unused until they were no longer fresh. With better forecasting, Monica wants to place orders that give her the best buying power while maintaining the quality of her products.
在过去的莫妮卡如期交付给她的袋装面粉和其他成分的企业一旦与“看上去低。”有时候，需求量不稳定的话，就不能保存库存材料的新鲜度。有了更好的预测，莫妮卡想能购买原材料越多的时候，同时保持其产品的质量。

The Sales Data worksheet shows the daily sales data of each of these products from the opening until the end of June 2002.
在销售数据电子表中记录了每种产品从2002年6月份开始至今日常销售数据：


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Monica created a PivotTable in Excel that summarizes the data for her three main products by week at the bottom of the Operations worksheet. By creating a PivotTable from the data, Monica can change the table to summarize her results by product, by time period, and more.
莫尼卡在Excel中创建的数据表，在不同的sheet表中注明了原料的名称，数据表是三个星期产品的数据。通过创建这个数据表，莫妮卡可以用表来概括她的产品，时间段等。

Monica wants to order monthly, one month in advance. The bakery has already received this month’s delivery, which she placed last month. This month, she must place the order that will be delivered at the end of this month for the next month, so she must forecast sales for the next two months. Since she is in week 173 of her business, the forecast is for weeks 174 to 181.
莫妮卡想分月采购，并提前一个月。该面包店已经收到这个月的交付，这是她将最后一个月情况。这个月，她必须把将要在这个月的下个月底前推出的顺序，因此她必须预测未来两个月内销售。一周以来，现在有173周的数据，需要预测是174至181周。

To forecast the sales for weeks 174 to 181: 对第174-181周的销售数据进行预测

1.In the Bakery.xls workbook, click the Operations tab.
The Operations worksheet appears.
1、在文档中，点击操作图表

2.Select one cell in the Historical Demand By Week PivotTable at the bottom of the worksheet.
2、在工作表底部的数据图表中选择历史数据中一个单元格

3.Start CB Predictor.
CB Predictor’s Intelligent Input automatically selects all the PivotTable data.
3、开始CB Predictor

4.Make sure:
•The cell range is selected correctly, with headers, dates, and data in columns (Steps 1 and 2)
•The time periods are in weeks with a seasonality of 52 weeks (Step 4)
•Multiple Linear Regression is off (Step 5)
•All time-series methods are selected (Step 6)
•The number of periods to forecast is 8 (Step 7)
•The only result selected is Paste Forecasts at the bottom of the PivotTable (Step 9)
4、确定：
       单元格被正确选取，包括标题、日期和数据
       时间周期根据周为单位是52周
       不选择多元线性回归分析
       所有的时间序列方法都选用
       需要预测的周期数是8周
       结果输出选择粘贴预测结果

5.Click Run.
The results paste to the end of the PivotTable as shown in Figure 4.3.
5、点击运行


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The last four weeks of forecast values for each data series are automatically summed and placed into the table at the top of the spreadsheet, in the Sales Forecast column (cells C9:C11). In this table, the monthly sales forecast is converted to the number of items sold and then into the weight of each product.
在销售量预测列中（C9-C11），每列数据有至少四周的预测数据会自动计算出来，并粘贴在工作表中。在这个图表中，预测每月销售额被转换为销售项目的数量，以及每个产品的重量。

The second table (below this top table) takes the total weight of each product (in cells C15, C19, C23) and calculates how much of each ingredient is required to produce that much product. The ingredients for each are then summed in the third table (below the second table) into the total amounts to order for the month (cells D31 to D34).
第二张图表中，包括每个产品的种重量（单元格C15,C19,C23），并计算了生产这些产品所需要的原材料是多少。每个原材料的情况在第三张表中。

Based on the forecast, Monica should order: 根据预测结果，莫妮卡可以进行以下操作：
•11,235 pounds of flour 需要11235磅面粉
•52 pounds of yeast 需要52磅酵母
•39 pounds of salt 需要39磅盐
•122 pounds of cheese 需要122磅奶酪


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漂在生活

Merry Christmas...

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Company finances公司财政

Monica is always concerned about the bakery’s month-to-month cash flow (on a percent of sales basis). Not only can CB Predictor help her manage her inventory, she can use it to predict her revenue and understand her cash flow situation better. Understanding the bakery’s cash flow can, in turn, help her time major capital expenditures better.
莫妮卡会对每个月的现金情况进行登记。这样不仅可以帮助她对预估库存进行管理，她可以用它来预测她的收入并使得她的现金流动情况变得更好。更好的了解面包店的现金流量，反过来，帮助她的更好地控制主要资本支出。

There are two major capital expenditures Monica is considering for the bakery: a flour silo and a delivery van. She wants to start construction on the silo in July and purchase the new delivery van in August. She needs to forecast when the bakery can safely pay for these projects or whether the bakery must finance them.
莫妮卡认为主要有两个方面的支出：面粉和运费。她想开始在7月份囤积一些油，在8月，购买一辆新的面包车。她需要预测何时可以实施这些项目计划或是否需要再等一段时间。

The bakery cash flow information is laid out on the Cash Flow worksheet, shown in the next figure.
在现金流量电子表中，给出了面包房现金流量情况：

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This worksheet has a PivotTable at the bottom that summarizes the sales data for the bakery’s three main products by month. You can forecast the next three months of revenue to decide when to attempt the capital expenditures.
工作表底部有一个数据透视表概括了3种面包主要的销售数据。你可以预测未来3个月的收入来决定决定费用的支出。

To forecast the next three months of revenue: 对往后三个月的预测：

1.In the Bakery.xls workbook, click the Cash Flow tab.
The Cash Flow worksheet appears.
1、点击现金流量表

2.Select one cell in the Historical Revenue By Month PivotTable at the bottom of the worksheet.
2、选择历史数据中的任意一个单元格

3.Start CB Predictor.
CB Predictor’s Intelligent Input automatically selects all the PivotTable data.
3、进行CB Predictor
CB Predictor会自动选择数据。

4.Make sure:
•The cell range is selected correctly, with data in rows and no dates or headers (Steps 1 and 2)
•The time periods are in months with a seasonality of 12 months (Step 4)
•All time-series methods are selected (Step 6)
•The number of periods to forecast is 3 (Step 7)
•The only result selected is Paste Forecasts At Cell $AQ$35 (Step 9)
•The pasted results are set to Paste In Rows
4、确定：
       单元格被正确选取，不包括标题、日期
       时间周期根据月为单位是12个月
       所有的时间序列方法都选用
       需要预测的周期数是3个月
       结果输出选择粘贴预测结果在单元格AQ35
       选择按行粘贴

5.Click Run.
The results paste into the table at the bottom of the worksheet, cells AQ36 to AS36 and also appear at the top of the worksheet (cells E4 to G4) as shown in Figure 4.6 on page 88.
5、点运行
结果在工作表的最下面粘贴在单元格AQ36-AS36，和E4-G4

The revenue forecasts for the next three months are used to calculate the percentage expenses in the second table.
用未来3个月的收入的预测来计算的第二个表中的百分比的费用。

The second table calculates the total expenses, and the third table calculates the necessary expenditure for each extraordinary item. Below these tables is the cash flow summary for the next three months, based on the forecasts. The net cash at the end of each month is what Monica is looking for.
第二个表计算总费用，第三个表计算每个特别项目所需开支。在这些表的基础上得到未来3个月的现金流量预测值。莫妮卡想要计算出在每个月底的净利润。

Based on the forecast, the bakery might be better off waiting another month, until September, before they try to purchase the van.

在这个预测基础上，面包房能更好的对其他月份的情况进行预测，在9月份之前希望能购买面包车。

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Human resources人力资源

Monica's Bakery is a labor-intensive operation that pays a very competitive wage. However, to maintain her target profitability, Monica must control her labor costs. She knows there are many things done around the bakery that could be done by expensive machinery, such as kneading, mixing, and forming. By accurately predicting her labor costs, she can decide when to invest in some of this equipment to keep her total expenses within budget.
莫尼卡的面包是一种劳动密集型的运作，需要大量的的工资。然而，为了维持她的目标利润，必须控制自己的劳动力成本。她需要支付很多东西，包括进行揉、捏、混合等昂贵的机器。准确地预测其劳动力成本，她可以决定何时在这部分设备投资，以保持在预算之内她的总开支。

From her interest in economics, Monica knows that a few key macro-economic figures drive labor costs, such as the Industrial Production Index, local CPI, and local unemployment. All of these figures are available on the Internet on a monthly basis from the Bureau of Labor Statistics and the Department of Commerce.
从她在经济利益，莫尼卡知道一些关键的宏观经济数字对人力成本是有影响的，如工业生产指数，当地物价指数，和当地的失业劳动力成本。这些数字在互联网上每月由劳工统计局和商务部发布。

Monica has created her Labor Costs worksheet with a PivotTable at the bottom that lists her average hourly wage for each month and the monthly numbers for these three indicators.
莫妮卡对人力成本做了一个数据图表，列出了每个月平均每小时的工资和每个月其他三个因素的数值。

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The average hourly wage depends on or is affected by the other three variables. Because of the dependency, Monica decides to use regression instead of time-series forecasting. For regression, the dependent variable is Monica’s Average Wage, and the other three are the independent variables.
每个小时的工资由其他三个数字决定。因为这个原因，莫妮卡决定使用回归分析的方法，而不是时间序列的方法。对于回归分析，因变量是莫妮卡的平均工资，其他三个三个因素是自变量。

To forecast the hourly wage using regression: 用回归到方法对人均工资进行预测：

1.In the Bakery.xls workbook, click the Labor Costs tab.
The Labor Costs worksheet appears.
   1、在工作表中，点击人力成本图表

2.Select one cell in the Economic Variables for Regression Analysis table at the top of the worksheet.
2、在工作表的最上面的回归分析图中，选择经济因素单元格

3.Start CB Predictor.
CB Predictor’s Intelligent Input automatically selects all the table data.
   3、开始CB Predictor

4.Make sure:
•The cell range is selected correctly, with headers, dates, and data in columns (Steps 1 and 2)
•The time periods are in months with a seasonality of 12 months (Step 4)
•Multiple Linear Regression is on (Step 5)
•The regression variables are defined: Monica’s Average Wage is a dependent variable, all the others are independent variables (Step 5)
•The regression method is set to Standard (Step 5)
•All time-series methods are selected (Step 6)
•The number of periods to forecast is 6 (Step 7)
•The only result selected is Paste Forecast (Step 9)
   4、确定：
           确定单元格选取正确，包括标题、日期等。
           时间周期选择以12个月为标准的月度周期
           选择使用多元线性回归方法
           回归因素选择：莫妮卡的每个月的平均工资为因变量（Y），其他因素为自变量（X）
           回归方法选择标准回归
           选择所有时间序列预测方法
           设定需要预测的时间周期为6个月
           选择只粘贴预测结果

5.Click Run.
The results paste at the bottom of the table (cells B51 to F56) as shown in Figure 4.8. Notice the results are defined as assumptions.
5、        点击运行
    预测结果会粘贴在图表下方，注意这个结果是一个假设定义的结果

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CB Predictor's HyperCasting technology first generates a regression equation to define the relationship between the dependent and independent variables. Second, it uses the time-series forecasting methods to forecast the independent variables individually. Third, CB Predictor uses those forecasted values to calculate the dependent variable values using the regression equation.
CB Predictor假设预测方法首先会定义自变量和因变量之间的关系得到一个回归方程。第二，会使用时间预测的方法对自变量单独进行预测。第三，CB predictor通过这些预测值，用回归方程来计算因变量的值。

The forecast cells of the independent variables are simple value cells. The forecast cells of the dependent variable are formula cells containing the regression equation and using the other values from the independent variables.
自变量的预测值是一个简单的值，因变量的预测值是包含了回归方程，并利用了自变量的预测值进行计算。

The average wage in December is used to calculate the total increase in her payroll. The increase is only 2%. With these results, Monica decides that labor costs will not increase enough over the next six months to justify a major equipment capital purchase.
12月度平均工资可以用来总支出的通体增长情况。这个增长值只有2%。通过这些结果，莫妮卡可以确定人力成本不会增加，未来6个月内有足够的资金购买新的设备。

6.Exit the Bakery.xls workbook without saving your changes.
6、保存数据，退出表格

CB Predictor Note: If you save your changes, you will overwrite the example spreadsheet.
CB Predictor注意：如果你想对变更进行保存，你需要将案例电子表格另外进行保存。


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lanj

要到最后一章了，呵呵，不能拖到2010{:8_307:}