Introduction
Particularly in the era of the internet, big data, and machine learning algorithms, statistics is frequently seen to be the purview of big business. By gathering a sample of information and extrapolating more information from that data, statistics aids us in determining uncertainty and forming strategies when faced with inadequate knowledge.
The use of statistics is widespread in all sectors of business, government, and academia. It is carried out with enormous resources and rigorous adherence to the scientific method. Statistical techniques and procedures are used in the work of educational administrators, political offices and authorities, company executives and marketing divisions, and scientific researchers.
But, it may also be utilised in the actual world and in individuals going about their regular lives. People are presented with inadequate information every day and must make decisions based on that knowledge. It may be the best route to go to work, the price to charge for a product they're selling, the duration of an activity, or the cost of an item they should buy at a physical or online store.
They take action to gather and arrange the data in a framework that can be analysed more readily and understood to conclude what has been found once they have chosen what they are seeking to find out and how they will get that knowledge. They could even utilise this information and the conclusions they draw to persuade others to agree with them on the issue.
5 Examples of How Statistics is Used in Real Life
Below mentioned are 5 examples of how statistics is used in real life:
Production Records for Products and Services - Any workplace that performs production analysis uses statistics extensively. Whether the organisation produces things or offers services, statistical models may be used in both scenarios for a variety of purposes, such as configuring and estimating worker performance, tracking the production of items, evaluating productivity and efficiency characteristics, etc. The factors that are taken into account in the statistical evaluation of efficiency and productivity at a firm primarily depend on the number of units of goods produced or tasks completed by the employees in a specific amount of time, the average number of sales attained by each employee, the number of new and retained customers, the rate and frequency of import and export of goods and services, the purchase and utilisation of resources, etc.
An organisation may manage the assets it already has or acquires in addition to increasing the production quality index and customer satisfaction ratio. This is made possible by keeping accurate records of all the goods and services produced. Also, doing statistical analysis on production data for products and services gathered before and after the execution of a certain plane aids researchers and investors in determining the scheme's risk and likelihood of success or failure. This usually gives the organisation's members a good indication of whether or not putting the new business method into use is a smart idea.
Analysis of Stock Market Data - A well-known use of statistical analysis in real life is stock market analysis. To determine the performance of a portfolio of various investments, the investor or consumer who is eager to make an investment in the market often gathers all the data that is readily accessible from the market and does research and analysis on it using various statistical models. This increases the user's chances of selecting the best option out of those that are offered. A variety of software, web sites, and mobile applications have been created and are accessible online to educate a person on the operation of the stock market and to appropriately lead him or her during the process of making an investment. This has been done to streamline the process.
Department of Quality at a Company - A common example of a real-world application where the use of statistical analysis can be clearly seen is in an organisation's quality control and assurance department. Simply put, a product's quality may be described as its suitability for the primary purpose for which it was intended and produced. Relevance, accuracy, accessibility, timeliness, reliability, comparability, coherence, manufacturing and selling costs, security, privacy, safety, flexibility, wear and tear rate, estimated life span, compatibility with other products, etc. are some of the criteria that help determine whether a product is fit for a given purpose. Using statistical measurements in quality inspections has several benefits.
For instance, cutting out the creation of defective items improves resource utilisation by conducting sophisticated statistical analysis of the commodities produced in an industry. Similar to this, the thorough and prompt quality analysis of real-time data ensures a noticeably better rate of production efficiency for the new product at the time of introduction and ensures the user has total control over the manufacturing process going forward. The statistical quality check report is also publicised, which increases consumer interest and confidence in the product.
Weather Prediction - Another example of a practical use for statistical analysis is weather forecasting. The main goal of weather forecasting is to estimate the likelihood that a specific event will occur based on a collection of previous or historical data. The historical trends related to weather and climate conditions, such as air temperature, pressure value, humidity magnitude, air quality index, cloud appearance, speed and direction of winds, precipitation levels and frequency, etc. are captured in form of sample datasets in order to perform weather forecasting with the highest level of efficiency. The algorithms that do the necessary calculation and analysis to reach conclusions are then given the collection of raw data. Inferential statistics essentially encompasses weather forecasting.
Health Records - Every day, large amounts of data are received by hospitals, medical facilities, research and development laboratories, etc. These data are often stored in a structured, unstructured, or semi-structured fashion. The information gathered by healthcare organisations is essential and has to be carefully managed. Medical records often contain details such as the patient's name, age, and gender, the date of admission, the disorder's kind, their medical history, the medical staff who have been assigned to them, the recommended medications and treatments, etc. The use of statistics in medical records aids in the proper organisation of patient information in a particular format, the separation of information or data points from one patient's record from another, the maintenance of current and easily accessible records at all times, the reduction of fatal error risks, the facilitation of the billing process, etc.
Conclusion
This statistics article aims to help readers understand the fundamental principles of statistics, whether they are experts or novices. But if you're interested in learning more, Skillslash can assist. If you want to learn about Statistics and its related concepts, we strongly advise attending courses like Skillslash's Advanced Data Science & AI course, Business analytics course, and others. The real-work experience offered by Skillslash is without a doubt among the greatest currently accessible, and it is most definitely worthwhile.
