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

lanj

从去年到上半年，一直在准备CMMI-4的评审。也因此接触了一些很不错的软件和统计工具，现在给大家介绍一种。Crystal Ball里面的CB Predictor预测工具。希望对大家都工作能有所帮助。

PS:由于是自己对英文教程的简单翻译，如有不足的地方，请大家见谅，凑合的看看啊～！


==============2010.07.19 管理员添加备注【开始】===============

该书的中英对照版电子书已发布，免费下载地址：http://step365.com/thread-2452-1-1.html

==============2010.07.19 管理员添加备注【结束】===============





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CB Predictor™  1.6—— User Manual使用手册
欢迎使用CB Predictor™


Welcome to CB Predictor, a powerful addition to the Crystal Ball suite of decision intelligence products!
欢迎使用CB Predictor，这是一个水晶球系统的附加的一个强大的决策产品！


Forecasting is an important part of many business decisions. Every organization needs to set goals, try to predict future events, and then act to fulfill the goals. As the timeliness of market actions becomes more important, the need for accurate planning and forecasting throughout an organization is essential to get ahead. The difference between good and bad forecasting can affect the success of an entire organization.
在商业决策中，预测是一个重要的部。每个企业都需要设立自己的目标，尝试去预测未来的发展趋势，然后采取行动去实现目标。随着及时的市场行动变的更为重要，这就需要我们在整个过程中能更准确的进行规划和预测。好的与坏的预测之间的差别是好的预测可以影响到一个组织的成功。


CB Predictor is an easy-to-use, graphically oriented forecasting add-in for Microsoft Excel spreadsheet users. If you have historical data in your spreadsheet, CB Predictor analyzes your data for trends and seasonal variations. It then predicts future values based on this information. You can answer questions such as, “What are the likely figures for next quarter’s sales?” or, “How much material do we need to have on hand?” With CB Predictor, you no longer need to pull these numbers out of thin air. Instead, you can rely on robust, statistically proven techniques to create these predictions accurately.
CB Predictor是一个易于使用的，自动加载在EXCEL中的预测向导图。如果在sheet中有历史数据，CB Predictor对数据的趋势和周期性变化进行分析，在历史数据的基础上预测未来的数值。您可以回答以下问题，如“下个季度的销售额可能是多少？”或者，“我们需要有库存在手头上？”使用 CB Predictor，你不需要再凭空的进行预测，你可以依靠完善的统计技术来进行准确的预测。


To get started, all you need is a spreadsheet containing historical data. From there, this manual guides you step by step, explaining forecasting terms and results.
若要开始使用CB Predictor，所有你需要一个包含历史数据的电子表格。本手册将引导您一步一步，解释条款和预测结果。



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Who should use this program?
谁会使用这一工具?


CB Predictor is for the planner and forecaster in every organization, from the sales manager predicting next quarter’s sales, to the marketing specialist forecasting the results of an advertising campaign, to the financial officer projecting likely revenue figures and cash flows. CB Predictor has been developed with a wide range of forecasting applications in mind.
CB Predictor对组织中计划和预测人员，对下一季度的销售量进行预测，对预测结果来预测广告投入量，和财务的现金收入和支出情况。



You don't need highly advanced statistical or computer knowledge to use CB Predictor to its full potential. All you need is a basic working knowledge of your computer and Microsoft Excel, plus a solid understanding of your own business fundamentals.
你不需要有非常先进的统计或计算机知识，利用CB Predictor充分发挥其潜力。您需要的是一些计算机和Microsoft Excel的基本知识，扎实的业务基础。



As an added benefit, you can automatically save CB Predictor forecasts as Crystal Ball assumptions for immediate use in powerful risk analysis models. See Chapter 5 for more information.
作为一个附加的好处是，可以直接对风险分析模型的建设自动生成CB Predictor预测。见第5章以获取更多信息。



CB Predictor runs on several versions of Microsoft Windows and Microsoft Excel. For a list of required hardware and software, see README.htm in the main Crystal Ball installation folder (by default, C:\Program Files\Decisioneering\Crystal Ball 7).
CB Predictor在多个版本的Microsoft Windows和Microsoft Excel中上运行。所需的硬件和软件，在README.htm中，主要水晶球安装文件夹（默认情况下， C：\ Program Files\ Decisioneering \ Crystal Ball 7)。

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How this manual is organized
手册是有哪些内容组成的？


•Chapter 1 — “Getting Started with CB Predictor”
启动 CB Predictor

This chapter contains two tutorials designed to give you a quick overview of CB Predictor’s features and to show you how to use it. Read this chapter if you need a basic understanding of CB Predictor.
本章包括两个案例来帮助你对CB Predictor的特性和如何使用进行快速的了解。


•Chapter 2 — “Understanding the Terminology”
了解术语

This chapter contains a thorough description of forecasting and statistical terms. Read this chapter carefully if your statistics background is limited or if you need a review of how terms are used in CB Predictor.
本章描述了预测和统计的条件。


•Chapter 3 — “Forecasting with CB Predictor”
使用 CB Predictor进行预测

This chapter contains step-by-step procedures for using all the features in CB Predictor.
本章描述了CB Predictor预测的一步一步的步骤和所有的特性。


•Chapter 4 — “Examples”
案例
This chapter contains example data from various fields.
本章包含各个领域的数据案例。


•Chapter 5 — “Using CB Predictor with Crystal Ball”
使用Crystal Ball 中的CB Predictor
This chapter contains descriptions of how to use CB Predictor with Crystal Ball. It also has some examples that are Crystal Ball-specific. The manual includes the following:
本章说明如何使用CB Predictor与水晶球。它还包括一些案例：



•Appendices
附录


•A — “The CB Predictor Wizard”
Settings for each tab of the CB Predictor wizard dialog.
A——CB Predictor 向导
CB Predictor向导每项步骤的设置


•B — “Time-Series Forecasting Method Formulas”
The formulas used for the time-series forecasting methods.
B——时间序列预测方法公式
使用时间序列预测方法的公式有哪些


•C — “Error Measure and Statistic Formulas”
The formulas used for time-series error measures and other statistics.
C——误差度量和统计的公式
使用时间序列预测方法的公式对误差和其他方面进行统计度量


•D — “Techniques for Finding Regression Coefficients”
How the program determines the coefficients of regression equations
D——回归系数的统计方法
如何确定回归方程中的回归系数


•E — “Regression Statistic Formulas”
The formulas used to calculate the statistics to gauge the quality of the regression and the coefficients.
E——回归统计公式
回归方程和回归系数的计算公式和统计方法


•F — “Error Messages”
A list of the most important CB Predictor error messages with directions for error recovery.
F——误差信息
罗列了CB Predictor中的几种重要的误差种类


•Bibliography
A list of related publications, including statistics textbooks.
•参考书目
有关的出版物的清单，包括统计教科书


•Glossary
A compilation of terms specific to CB Predictor as well as statistical terms used in this manual.
术语
CB Predictor方面的相关术语，以及在本手册中使用的统计术语汇编。


•Index
An alphabetical list of subjects and corresponding page numbers.
序号
手册和相应的页码内容字母排列顺序


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lanj

{:8_305:}听着怎么感觉毛毛的～
看来要加油了，否则对不起大家啊{:8_307:}

lanj

Chapter 1   第一章            
Getting Started with CB Predictor  

In this chapter在这一章中会涉及到：
•What is time-series forecasting?
      什么是时间序列预测？
•Shampoo Sales tutorial
      香波销售案例
•How CB Predictor works
      CB Predictor如何工作
•Toledo Gas tutorial
      托莱多燃气公司案例

This chapter has two tutorials, a short one and a longer one, that provide an overview of CB Predictor’s features. The first tutorial, Shampoo Sales, is ready to run, using most of the defaults. The results forecast the next quarter’s worth of shampoo sales。
本章有两个案例，一个简单的一个复杂的，这两个案例是帮助我们更好的对CB Predictor的特性进行了解。在第一个香波案例中，有许多的误差，它是对下一个季度香波的销售值的预测。

The second tutorial, Toledo Gas, uses regression, previews the results, and customizes some features. The results predict the next year’s worth of residential gas usage for Toledo.
第二个Toledo Gas的案例，使用了回归分析，对结果进行评审，是对Toledo Gas明年的使用情况的预测.

Now spend some time learning how CB Predictor can help you forecast the future。
现在花费一些时间来学习如果使用CB Predictor来帮助你预测未来。

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What is time-series forecasting? 什么是时间序列预测？
“Prediction is very difficult, especially if it’s about the future.”- Niels Bohr Nobel laureate in Physics
“预测是非常困难的，尤其是对未来的预测”——Niels Bohr 诺贝尔物理学奖获得者

How often are you asked to estimate future sales? Staffing requirements? Budget items? Do you need to predict numbers for the next year using historical numbers that are higher in the summer than the winter? Or numbers that rise and fall with the Dow Jones industrial average? if so, CB Predictor can help.
多久询问一次未来的销售量？员工配置需求？财政预算？你是否需要用比冬季更高的夏季的历史数据来预测明年的数据？或者是道琼斯工业平均指数的上涨和下跌？如果是的话，CB Predictor可以帮助你。

If you have historical time-series data, you can use CB Predictor to examine your historical data and predict future trends. You no longer have to assume that sales will be same as last quarter or that you will spend 10% more next year on expenses than this year. CB Predictor applies a battery of sophisticated statistical methods to your data series to find results that meet the strictest confidence requirements.
如果你有有时间顺序的历史数据，你可以使用CB Predictor工具来对历史数据进行评估并对未来的趋势进行预测。你不需要再去假设你的销售额会和上个季度的一样，也不需要再花费比去年多10%的开支。CB Predictor工具有一整套成熟的统计方法对你的历史数据进行分析，并根据严格的要求得到预测的结果。

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CB Predictor uses two types of forecasting: time-series forecasting and multiple linear regression. Time-series forecasting breaks down your historical data into four components: level, trend, seasonality, and error. CB Predictor analyzes each of these components and then projects them into the future to predict likely results.
CB Predictor使用两种类型的预测方法：时间序列预测和多元线性回归方法。时间序列预测方法将你的历史数据从四个方面进行分析：水平、趋势、周期性和误差。CB Predictor对每个方面进行分析，并利用他们来预测未来最有可能的结果。

When you know that outside influences have an effect on the variable you want to forecast, you need regression. Regression takes historical data from the influencing variables and determines the mathematical relationship between these variables and your target variable. It then uses time-series forecasting methods to forecast the influencing variables and combines the results mathematically to forecast your target variable.
当你知道需要预测的变量收到外部因素的影响时，在预测是需要进行回归。回归是要对找到有影响因素的历史数据，并找到这些因素和预测变量之间的相互数学关系，然后运用时间时间序列预测的方法结合变量和目标变量之间的相互关系来进行预测。

After finding the best forecast for your data, CB Predictor pastes the forecasted values into your spreadsheet. You can also request detailed output that includes statistics, charts, reports, and PivotTables. CB Predictor can also create your forecasted values as Crystal Ball assumptions, ready for a “what-if” simulation.
当从数据中找到了最佳的预测值收，CB Predictor将预测结果粘贴到sheet表格中。你也可以要求详细的输出结果，包括统计数据、图表、报告和Pivto图。CB Predictor预测的数据可以作为水晶球的假设，为准备模拟做准备。

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Shampoo Sales tutorial香波销售案例
The easiest way to understand what CB Predictor does is to apply it to a simple example. In this example, you are sales manager for Tropical Cosmetics Co. The company’s latest product, shampoo with tropical ingredients, has been in the marketplace for almost a year now. The vice president of marketing wants you to forecast the rest of the year’s sales of shampoo and decide whether to recommend investing in advertising or enhancements for this product.
CB Predictor最简单的理解方法就是进行案例的演示。在这个案例中，你是Tropical Cosmetics Co.公司的销售经理，这家企业最新的产品是有热带成分的洗发香波，该产品已经在市场是销售了近一年的时间。负责营销的副总希望你对今年剩下的时间的销售量进行预测，以便来决定是否在广告投入和产品改良中继续投资。

You have the weekly sales numbers for the last nine months.
你有过去9个月的每周的销售数据。

To begin the tutorial: 案例开始：
1.Start Crystal Ball and Excel.
1、打开水晶球（crystalball）和excel表格。
2.Open the Shampoo Sales spreadsheet from the Examples folder.
2、在案例文件夹中打开香波销售量的电子表格。
By default, the file is stored in this folder: C:\Program Files\Decisioneering\Crystal Ball 7\Examples\CB Predictor Examples.
该表格的默认地址是C:\Program Files\Decisioneering\Crystal Ball 7\Examples\CB Predictor Examples.


ps:我将Shampoo sales的表格上传给大家看看

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Shampoo Sales.xls

lanj

In this spreadsheet, there is one column of Tropical shampoo sales data next to a column with dates from January 1, 2004 until September 23, 2004. You need to forecast sales through the end of the year, December 31, 2004.
在这张电子表格中，一列是热带香波的销售量的数据，边上一列是数据对应的时间，从2004年1月1日到2004年9月23日。你需要预测的是从现在到年底2004年12月31日的销售数据。

3.Select cell B4.
Selecting any one cell in your data range, headers, or date range initiates CB Predictor’s “Intelligent Input” to select all the filled, adjacent cells.
3、选择单元格B4
选择表格范围中任意一个单元格，以选择整个数据表格。

4.Select Run > CB Predictor.
4、选择Run>CB Predictor
The CB Predictor dialog, or wizard, opens to the Input Data tab as shown in Figure 1.2.
出现CB Predictor的对话框，按照图1.2显示的选取输入的数据范围。

Note: This command is only available if no simulation is running and the last run was reset. If necessary, wait for a simulation to stop or reset the last simulation.
注：此命令仅适合没有进行模拟运行的数据，如果有，需要将模拟停止或重新进行重置。



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When you select any one cell in the data range before you start the wizard, CB Predictor’s Intelligent Input guesses:
当你选择了数据表格中的任意一个单元格后再开始向导，CB Predictor会自动选择输入的范围：

•Your data series (in this case, A3:B42)
你的数据系列是在A3:B42的范围内

•Whether your data are in columns or rows
数据是按列或者按行排列

•Whether you have headers at the beginning of your data
你是否需要在开头开始数据

•Whether your first column or row contains dates or time periods
在第一列或第一行中是否包括数据活时间周期

5.Click Next.
5、点击Next

The Data Attributes tab appears as shown in Figure 1.3.
数据会像图1.3一样显示在向导卡中


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6.Under Step 4:
a. Select “weeks” from the Data Is In list.
b. Set the data to have no seasonality.
You have less than two complete seasons (cycles) of data, so cannot use seasonality.
6、第四步：
   a、在Data is in表格中选择“周”
   b、选择没有周期性
   如果选择周期性的话，你必须要有两个以上的完整周期的数据。

7.Under Step 5, make sure that Use Multiple Linear Regression is not checked.
You did not choose regression because you have only one series of data, so there are no dependencies between series requiring regression.
7、第五步，确认没有选择多元线性回归分析
如果只有一组数据的话，不需要选择线性回归，

8.Click Next.
8、点Next
The Method Gallery tab appears as shown in Figure 1.4.
图1.4显示了有哪些统计方法：


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9.Click Select All.
This selects all the time-series forecasting methods, but CB Predictor doesn’t use the seasonal methods, since you indicated that your data were not seasonal.
CB Predictor forecasts your values using each of the selected methods and ranks them according to how well they fit the historical data. CB Predictor uses the seasonal methods as well as the nonseasonal methods if you indicate on the Data Attributes tab that your data series have seasonality.
9、点击“select all”
选择了所有的时间序列的方法，但是如果你的数据没有周期性，CB Predictor不使用周期性方法。
CB Predictor使用每个选择的方法来预测数值，并将产生预测值的最佳方法进行排序，如何你的数据系在数据分布图中显示的是有周期性的，那么CB Predictor也会选择周期性的方法，而不是非周期性的。

10.Click Next.
The Results tab appears as shown in Figure 1.5. The only output selected by default is Paste Forecast, which adds the forecasted values to the end of your historical datas shown in Figure 1.5.
10、点Next
在图1.5中显示了结果的图表，唯一输出的结果是粘贴预测，这种预测方法会将预测值粘贴到历史数据的最后面。


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11.Under Step 7, forecast the weekly sales for the rest of the year by entering 13 in the field.
11、第七步，在表格中填入需要预测的今年剩下的时间的销售量的周数，输入13周。

12.Click Preview.
The Preview Forecast dialog appears. It presents a graph with historical data, fitted data, forecast values, and confidence intervals as shown in Figure 1.6.
12、点击Preview
Preview Forecast对话框出现，这张图表中显示了历史数据、合适的数据、预测数据和置信区间的范围。





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13.In the Preview Forecast dialog, click the Method field.
The field lists all the methods CB Predictor tried, in order from the best-fitting method (designated by the word “Best”) to the worst-fitting method. CB Predictor calculates the forecasted values from the method that best fits the historical data. In this case, the method is Double Exponential Smoothing.
13、在Preview Forecast对话框中点击Method field。
在fiels清单中有CB Predcitor所有的预测方法，按照最佳到最差的方法顺序进行排列。CB Predictor从最佳的方法中历史数据情况计算出预测值，该图中最佳的方法是双边指数平滑。

The forecasted values appear as a blue line extending to the right of the historical data (green) and the fitted values also in blue). Above and below the forecasted values is the confidence interval (in red), showing the 5th and 95th percentiles of the forecasted values.
绿色的线代表的是历史数据，历史数据的最佳值对应的是与历史数据重合的蓝色的线条，在边上的蓝色线条代表的是预测值的趋势情况。在预测值的蓝色线条上下的红色线条是置信区间的范围，即预测值的5%-95%的可能性。

14.Click Run.
The program pastes the forecasted values at the end of the historical data (in bold), extending the date series as well. The forecasted values were forecasted using the best method, as shown in the Preview dialog.
Figure 1.7 Pasted shampoo sales values
14、点击Run
在历史数据后面粘贴预测值，该预测值是在Preview Forecast图中显示的最佳的方法得到的。


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