2 - AGEC 4273 Agricultural Price Analysis Instructor: Dr....

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AGEC 4273 Agricultural Price Analysis Instructor: Dr. Hector Zapata Basic Statistics for Price Analysis Introduction Descriptive statistics are some of the most basic tools used for statistical data analysis, and their application to price analysis is not an exception. Statistical measures such as the mean, standard deviation, minimum and maximum values, coefficient of variation, and coefficient of linear association (correlation coefficient) are often used to describe price behavior. Prior to conducting any statistical analysis, it is good practice to construct graphs of data as a means of learning price patterns that prices follow over time and also for checking price data quality (making sure that there are no obvious errors in the price data). Three methods of analysis, tabular, graphical and statistical, are covered in this lecture. Illustrations are provided using Excel, the spreadsheet program that will be used to conduct research for the newsletter project. At the end of this lecture, readers should have some proficiency on the fundamentals of graphical analysis, calculation of descriptive statistics in Excel, analysis of descriptive statistics, and writing descriptive analyses for technical reports. Tabular Method Tables should be descriptive enough for the reader to know what data the table contains, the time period, and the units of measurement for each variable; this information is placed on the title. Data are often collected at local, state, regional, national or international level. This information should be specified in the title also. The title is followed by a header; this could be two horizontal lines going across the page with one or more spaces in between the lines to allow for column names. Units of measurement are included, either inside the header or in the body of the table. The body of the table is the one containing the numbers that are reported. Another horizontal line is added at the bottom of the body of the table to delimit the end of the data set. The data source(s) are included in a smaller font at the bottom of the table; cite sources in such a way that the reader can go to them and easily locate the information that the table contains. Finally, footnotes are often used to describe details about the table that help clarify how variables are measured, whether data transformations have been applied, specific description of certain variables, and many other important details. An example for U.S. corn exports is provided below. The data was downloaded from the USDA/ERS website: 1
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http://www.ers.usda.gov/Data/feedgrains/StandardReports/YBtable22.htm and the screen that comes up at this link looks like: Screen 1. An Internet screen from USDA/ERS website. These data were downloaded to Excel and a table was built (table 1 below). The title of Table 1 is descriptive of its contents (U.S. corn exports to main destinations for the selected years). The column labels and content in this table should coincide with those in the original source. Although this is usually a
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2 - AGEC 4273 Agricultural Price Analysis Instructor: Dr....

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