1. Chapter 1 Data and Statistics
Applications in Business and Economics
Data
Data Sources
Descriptive Statistics
Statistical Inference

2. Applications in Business and Economics
Accounting
Public accounting firms use statistical sampling procedures when conducting audits for their clients.
Finance
Financial advisors use a variety of statistical information, including price-earnings ratios and dividend yields, to guide their investment recommendations.
Marketing
Electronic point-of-sale scanners at retail checkout counters are being used to collect data for a variety of marketing research applications.

3. Applications in Business and Economics
Production
A variety of statistical quality control charts are used to monitor the output of a production process.
Economics
Economists use statistical information in making forecasts about the future of the economy or some aspect of it.

4. Data Elements, Variables, and Observations
Qualitative and Quantitative Data
Cross-Sectional and Time Series Data

5. Elements, Variables, and Observations
Data are the facts and figures that are collected, summarized, analyzed, and interpreted.
The data collected in a particular study are referred to as the data set.
The elements are the entities on which data are collected.
A variable is a characteristic of interest for the elements.
The set of measurements collected for a particular element is called an observation.
The total number of data values in a data set is the number of elements multiplied by the number of variables.

6. Qualitative and Quantitative Data
The statistical analysis that is appropriate depends on whether the data for the variable are qualitative or quantitative.
Qualitative data are labels or names used to identify an attribute of each element.
Quantitative data indicate either how much or how many.
Quantitative data are always numeric.
Qualitative data can be either numeric or nonnumeric.
Ordinary arithmetic operations are meaningful only with quantitative data.

7. Cross-Sectional and Time Series Data
Cross-sectional data are collected at the same or approximately the same point in time.
Example: data detailing the number of building permits issued in June 1999 in each of the counties of Texas
Time series data are collected over several time periods.
Example: data detailing the number of building permits issued in Travis County, Texas in each of the last 36 months

8. Data Sources Existing Sources
Data needed for a particular application might already exist within a firm. Detailed information is often kept on customers, suppliers, and employees for example.
Substantial amounts of business and economic data are available from organizations that specialize in collecting and maintaining data.
Government agencies are another important source of data.
Data are also available from a variety of industry associations and special-interest organizations.

9. Data Sources
Internet
The Internet has become an important source of data.
Most government agencies, like the Bureau of the Census ( make their data available through a web site.
More and more companies are creating web sites and providing public access to them.
A number of companies now specialize in making information available over the Internet.

10. Data Sources Statistical Studies
Statistical studies can be classified as either experimental or observational.
In experimental studies the variables of interest are first identified. Then one or more factors are controlled so that data can be obtained about how the factors influence the variables.
In observational (nonexperimental) studies no attempt is made to control or influence the variables of interest.
A survey is perhaps the most common type of observational study.

11. Data Acquisition Considerations
Time Requirement
Searching for information can be time consuming.
Information might no longer be useful by the time it is available.
Cost of Acquisition
Organizations often charge for information even when it is not their primary business activity.
Data Errors
Using any data that happens to be available or that were acquired with little care can lead to poor and misleading information.

12. Numerical Measures and Index Numbers
In addition to tabular and graphical displays, numerical descriptive statistics are used to summarize data.
The most common numerical descriptive statistic is the average (or mean).
Index numbers are numerical descriptive statistics typically designed to help individuals better understand current business and economic conditions.
The most widely known index is the Consumer Price Index (CPI) which the primary measure of the cost of living in the U.S.

13. Descriptive vs. Inferential Statistics
Descriptive statistics are the tabular, graphical, and numerical methods used to summarize data.
Statistical inference is the process of using data obtained from a small group of elements (the sample) to make estimates and test hypotheses about the characteristics of a larger group of elements (the population).