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    Ayşe Demir

    İstanbul, Türkiye

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    Data and Statıstıcs

    Published: October 24, 2018

    Applications in Business and Economics Data Data Sources Descriptive Statistics Statistical Inference

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    Data and Statıstıcs

    • 1. Data and Statıstıcs Data and Statıstıcs
    • 2. Data and Statıstıcs Data and Statıstıcs •Applications in Business and Economics •Data •Data Sources •Descriptive Statistics •Statistical Inference
    • 3. Applıcatıons ın Busıness and Economıcs Applıcatıons ın Busıness and Economıcs •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.
    • 4. Applıcatıons ın Busıness and Economıcs Applıcatıons ın Busıness and Economıcs •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.
    • 5. Data Data •Elements, Variables, and Observations •Qualitative and Quantitative Data •Cross-Sectional and Time Series Data
    • 6. Elements, Varıables, and Observatıons Elements, Varıables, and Observatıons •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.
    • 7. Qualıtatıve and Quantıtatıve Data Qualıtatıve and Quantıtatıve 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.
    • 8. Cross-Sectıonal and Tıme Serıes Data Cross-Sectıonal and Tıme Serıes 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
    • 9. Data Sources 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.
    • 10. Data Sources Data Sources •Internet •The Internet has become an important source of data. •Most government agencies, like the Bureau of the Census (www.census.gov), 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.
    • 11. Data Sources 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.
    • 12. Data Acquısıtıon Consıderatıons Data Acquısıtıon Consıderatıons •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.
    • 13. Numerıcal Measures and Index Numbers Numerıcal 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.
    • 14. Descrıptıve vs. Inferentıal Statıstıcs Descrıptıve vs. Inferentıal Statıstıcs •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).