Computing Branch Probabilities Using Bayes’ Theorem

In Section 19.3 the branch probabilities for the PDC decision tree chance nodes were specified in the problem description. No computations were required to determine these probabilities. In this section we show how Bayes’ theorem can be used to compute branch probabilities for decision trees. The PDC decision tree is shown again in Figure

Price Relatives

The simplest form of a price index shows how the current price per unit for a given item compares to a base period price per unit for the same item. For example, Table 20.1 reports the cost of one gallon of gasoline for the years 2000 through 2017. To facilitate comparisons with other years,

Aggregate Price Indexes

Although price relatives can be used to identify price changes over time for individual items, we are often more interested in the general price change for a group of items taken as a whole. For example, if we want an index that measures the change in the overall cost of living over time, we

Computing an Aggregate Price Index from Price Relatives

In Section 20.1 we defined the concept of a price relative and showed how a price relative can be computed with knowledge of the current-period unit price and the base-period unit price. We now want to show how aggregate price indexes like the ones developed in Section 20.2 can be computed directly from information

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Some Important Price Indexes

We identified the procedures used to compute price indexes for single items or groups of items. Now let us consider some price indexes that are important measures of business and economic conditions. Specifically, we consider the Consumer Price Index, the Producer Price Index, and the Dow Jones averages. 1. Consumer Price Index The Consumer

Deflating a Series by Price Indexes

Many business and economic series reported over time, such as company sales, indus­try sales, and inventories, are measured in dollar amounts. These time series often show an increasing growth pattern over time, which is generally interpreted as indicating an increase in the physical volume associated with the activities. For example, a total dollar amount

Price Indexes: Other Considerations

In the preceding sections we described several methods used to compute price indexes, discussed the use of some important indexes, and presented a procedure for using price indexes to deflate a time series. Several other issues must be considered to enhance our understanding of how price indexes are constructed and how they are used.

Quantity Indexes

In addition to the price indexes described in the preceding sections, other types of indexes are useful. In particular, one other application of index numbers is to measure changes in quantity levels over time. This type of index is called a quantity index. Recall that in the development of the weighted aggregate price index

Philosophies and Frameworks of Statistical Methods for Quality Control

In the early twentieth century, quality control practices were limited to inspecting finished products and removing defective items. But this all changed as the result of the pioneering efforts of a young engineer named Walter A. Shewhart. After completing his doctorate in physics from the University of California in 1917, Dr. Shewhart joined the

Statistical Process Control

In this section, we consider quality control procedures for a production process whereby goods are manufactured continuously. On the basis of sampling and inspection of produc­tion output, a decision will be made to either continue the production process or adjust it to bring the items or goods being produced up to acceptable quality standards.

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Acceptance Sampling

In acceptance sampling, the items of interest can be incoming shipments of raw materi­als or purchased parts as well as finished goods from final assembly. Suppose we want to decide whether to accept or reject a group of items on the basis of specified quality characteristics. In quality control terminology, the group of items

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Using EViews for Principles of Econometrics

This manual is a supplement to the textbook Principles of Econometrics, 3rd Edition, by Hill, Griffiths and Lim (John Wiley & Sons, Inc., 2008). It is not in itself an econometrics book, nor is it a complete computer manual. Rather it is a step-by-step guide to using EViews for the empirical examples in Principles

Starting EViews

To launch EViews double click the EViews 6 SV icon on the desktop, if one is present. It should resemble Alternatively, select EViews from the Windows Start Menu. When EViews opens you are presented with the following screen Across the top are Drop Down Menus that make implementing EViews procedures quite simple. Below the

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The EViews Help System

Click Help on the EViews menu The resulting menu is 1. EViews help topics First, click on EViews Help Topics. Select Getting Started (Student Version) to obtain basic information about the Student Version of EViews. Selecting User’s Guide/EViews Fundamentals opens a list of chapters that can take you through specifics of working with EViews.

Using a EViews Workfile

As noted earlier all the data for the book Principles of Econometrics is provided as EViews worhfiles. These will be used starting in Chapter 2. To illustrate the basic functioning of EViews we will use an example provided with EViews. Click on Help/EViews Help Topics/User’s Guide/EViews Fundamentals/A Demonstration. The demonstration starts by importing data

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Examining Several Series with EViews

Rather than examining one series at a time we can view several. In the workfile window select the series Ml and then while holding down the Ctrl-key select the PR series. Double click inside the blue area to open what is called a Group of variables. Click on Open Group. A spreadsheet view of

Using the Quick Menu of EViews

The spreadsheet view of the data is very powerful. Another key tool is the Quick menu on the EViews workfile menu. The options shown are 1. Changing the sample By selecting Sample from this menu we can change the range of sample observations. Change the sample to 1952:1 to 2003:4 and click OK. 2.

Using EViews Functions

Now we will explore the use of some EViews functions. Select Help/Quick Help Reference/Function Reference. 1. Descriptive statistics functions Select Descriptive Statistics from the list of material links. Some of the descriptive statistics functions listed there are on the next page. In this table of functions you will note that these functions begin with

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The Simple Linear Regression Model by using EViews

In this chapter we introduce the simple linear regression model and estimate a model of weekly food expenditure. We also demonstrate the plotting capabilities of EViews and show how to use the software to calculate the income elasticity of food expenditure, and to predict food expenditure from our regression results. 1. OPEN THE WORKFILE

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Interval Estimation and Hypothesis Testing by using EViews

1. INTERVAL ESTIMATION For the regression model y = β1 +β2x + e, and under assumptions SR1-SR6, the important result that we use in this chapter is given in equation (3.3) of POE.             ’ Using this result we can show that the interval bk ± tcse(bk) has probability 1-a of containing the true