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# What is the importance of statistics in economics?

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Statistics are a methodology necessary in the field of statistics and are used to collect, analyze and evaluate data. Economics depends heavily on the use of statistics.

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Credit: Open Data Institute CC-BY-SA 2.0

Economics is defined as the study of how people behave with regard to the production and consumption of goods. As a social science, economics attempts to describe trends in consumer markets, such as wealth acquisition and transfer. There are two forms of economics:

• Macroeconomics: analysis of large-scale economic activity, such as within a country or international market
• Microeconomics: analysis of small-scale economic activity, such as between individuals and corporations

There are various themes studied within both forms of economics, including costs, production, consumption, and the rationales behind individual, corporate, national and international trade. In order to develop hypotheses around the various topic areas, economists make use of statistics and are able to compare information. Economic statistics involve quantitative data that describe either past or present trends. The data may be presented in various ways:

• Time-related: to show trends and changes that occurred across a specific period of time, for example, unemployment rates or housing costs during a 10-year period
• Cross-section: to show trends and changes within a specific period of time, for example, job statistics for current year college graduates

Economic statistical data sets include information about measurement, sample sizes, collection procedures and analysis processes. The data are often published for public use, such as through the United States Census or for private use, such as intra-company data used for decision-making.

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## Related Questions

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People use statistics daily for weather forecasts, predicting disease, preparing for emergencies, medical research, political campaigns, tracking sales, genetics, insurance, the stock market and quality testing. Statistics lends credibility to these industries and makes it easier to track different things in the industry.

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Standard deviation is a measure of variation in data. It allows comparison between two or more sets of data to determine if their averages are truly different. For example, if the average salaries in two companies are \$90,000 and \$70,000 with a standard deviation of \$20,000, the difference in average salaries between the two companies is not statistically significant.

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According to HealthKnowledge, the main disadvantage of parametric tests of significance is that the data must be normally distributed. The main advantage of parametric tests is that they provide information about the population in terms of parameters and confidence intervals. Another advantage of parametric tests is that they are easier to use in modeling (such as meta-regressions) than are non-parametric tests.