Why does statistics matter

Statistics today is central to almost all scientific disciplines. Siddharth Kalla May 12, Why Statistics Matter?. Retrieved Nov 11, from Explorable. The text in this article is licensed under the Creative Commons-License Attribution 4.

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One of the most important sub-fields of statistics is probability. This is the field that studies how likely events are to happen. By having a basic understanding of probability, you can make more informed decisions in the real world. A p-value is the probability of observing a sample statistic that is at least as extreme as your sample statistic, given that the null hypothesis is true.

For example, suppose a factory claims that they produce tires that have a mean weight of pounds. An auditor hypothesizes that the true mean weight of tires produced at this factory is different from pounds so he runs a hypothesis test and finds that the p-value of the test is 0.

This tells us that obtaining the sample data that the auditor did would be pretty rare if indeed the factory produced tires that have a mean weight of pounds. Thus, the auditor would likely reject the null hypothesis that the true mean weight of tires produced at this factory is indeed pounds.

The value for a correlation coefficient always ranges between -1 and 1 where:. By understanding these values, you can understand the relationship between variables in the real world. For example, if the correlation between advertisement spending and revenue is 0. As you spend more money on advertising, you can expect a predictable increase in revenue. Another important reason to learn statistics is to understand basic regression models such as:.

Each of these models allow you to make predictions about the future value of some response variable based on the value of certain predictor variables in the model. For example, multiple linear regression models are used all the time in the real world by businesses when they use predictor variables such as age, income, ethnicity, etc. Similarly, logistics companies use predictor variables like total demand, population size, etc. Another reason to study statistics is to be aware of all the different types of bias that can occur in real-world studies.

By having a basic understanding of these types of biases, you can avoid committing them when performing research or be aware of them when reading through other research papers or studies. Many statistical tests make assumptions about the underlying data under study. The following articles share the assumptions made in many commonly used statistical tests and procedures:.

Another reason to study statistics is to understand the concept of overgeneralization. Check out the following articles to gain a basic understanding of the most important concepts in introductory statistics:. Descriptive vs. It can help improve the design of future policy measures and enable a more timely policy response. Collecting detailed statistical information can be quite challenging, especially as regards choosing methodologies and calculation methods that ensure comparability across countries.

A further challenge is obtaining information from entities that operate outside the banking system and that may have an impact on the financial system, and therefore also on monetary policy. Furthermore, the confidentiality of individual data must always be ensured, especially in the case of supervisory data used in activities conducted jointly with external parties. Data harmonisation is also critical as it allows for meaningful results and reliable comparisons.

For example, we can be confident about the accuracy of the inflation data used because they are derived from national data based on a common set of definitions and classifications, in other words the same sort of shopping basket of goods and services. Harmonised and standardised statistics make it easier for policymakers to design timely and targeted policy responses to economic developments in the euro area.

At the same time, statistics are made publicly available for banks, companies, households and other reporting agents to use in their own data analysis and benchmarking. Naturally, the euro area is the main focus of the statistics collected, developed and prepared by the ECB.

We also share key data. You can obtain a wide range of statistics from either the Euro area statistics website — which presents statistics visually, interactively and in formats that are easy to embed in digital media — or our comprehensive Statistical Data Warehouse. This is possible thanks to the close cooperation between the ECB and the national central banks, as well as with EU institutions and national and international statistical offices, including the EU statistical office Eurostat.

Statistics are essential for making informed decisions. We provide a wide range of official statistics on the health of the economy.

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