What is Statistical Analysis and why is It Important for Business?


What is Statistical Analysis and why is It Important for Business?

Many scientists give define that statistical analysis is a component of data science. Firstly, let’s see how modern researchers explain the meaning of statistics.

In 2001, William S. Cleveland, American computer scientist, Professor of Statistics and Professor of Computer Science at Purdue University (Indiana), specified statistics as the study of the collection, analysis, interpretation, presentation, and organization of data. Due to such approach, we can define it as the science of collecting data and exploring future trends. Nowadays, many business companies improve their activities on this basis. It’s the best way to identify new trends and understand customers’ needs.

How Does It Work?

A successful business owner or company management has a great intuition, but it is not enough for taking a crucial decision. For example, statistical analysis in retail business can be used with a purpose to identify patterns of customer’s data and, as a result, increase sales, get new consumers, and improve customer experience. It’s also useful in banking, manufacturing and sports industries. Getting information about upcoming trends and making some hypotheses is a great benefit.

After collecting statistical data, it is also possible to summarize received visual data and make final charts or get average indexes. This process is everywhere around us: many key decisions rely on the results of this analysis. It provides decision-makers and business managers of all levels with the necessary tools to make business more productive. In management, it is a solid basis to get conclusions and present facts. Furthermore, the central part of experiments was performed in response to the fundamental research methodology in social science, natural science, and even engineering.

Statistical Analysis Types

As we mentioned above, it is possible to describe statistical analysis data as the number of variables. Sometimes, received visual data can be univariate or multivariate, and the choice of the right statistical technique depends on the number of variables.

The researchers mark two primary types:

  1. Descriptive type. Commonly, this type is used to describe basic information by summarizing. For example, if a retail business company needs to choose the right marketing segment and hold an opinion poll, the results are processed with the help of descriptive statistical analysis. However, it’s impossible to make any decision or conclusion on this basis. This type was created to make a simple interpretation of the data. 
  2. Inferential type. It is used to study the relationship between variables and make conclusions or predictions. It makes it possible to create a hypothesis and go further to the decisions.

There are also five additional types of statistical analysis, which are also very important and useful to everyone, who works with visual data, including company management.

  • Predictive analytics: the primary users are marketing consulting companies, financial, and insurance companies. This type allows them to minimize possible risks and predict what might happen.
  • Prescriptive analytics: it plays an essential role in management, as it helps to identify the best decision in the current situation and gives recommendations to decision-makers.
  • Causal analytic: sometimes, it is more necessary to view the reasons for something than analyze the results. Some things in business lead to failures. Therefore, good managers are committed to correct done mistakes and never repeat them.
  • Exploratory data analytic (EDA): mostly data scientists use this type as it helps to dig deeper into details and relationships, especially if the purpose is to find new connections or check a hypothesis.
  • Mechanistic data analytic: it allows us to understand the changes in given items that can influence other variables. This type is suitable for experts, like biologists.

What Statistical Methods are Popular?

The simplest methods are created to gather general information. Today it’s elementary to do, using social networks: Facebook, Instagram or Twitter. It helps to understand people’s motivation, their wishes, daily habits, preferences, and more. This information can be helpful for marketing specialists or company management who want to receive feedback on their advertising and business activity. It works well in advertisement settings because by using this science, it is easier to target the audience and attract more customers. This statistical method is also called behavioral or cohort analysis.

We remember statistical regression models from school time. It’s also not so difficult to use, and it is claimed to view strong or weak relationships. The next method you too can remember is a mean method, which is also well-known as average. It is easy to calculate, and it helps to determine common trends. If you need to view a spread of data, it is better to use the standard deviation method. The Greek letter sigma can also familiar to you from high school, and you probably remember it.

The modern scientists mark more than 10 techniques, which are the must for a good data statistical analyst. The data scientist is ranked #1 in Glassdoor's rate of 25 Best Jobs in the US. Using machine learning and these 10 special techniques, statistical data analysts are on the top of the wave of innovations and world technical progress.

The Role for Management and Business

If you’ve decided to become a successful business owner, the course of business statistics is obligatory. Such knowledge is useful in studying finances, audit, and marketing research. Many business owners have to make decisions on their hook. Using statistics, you can know more about how to organize data, use statistical tools to analyze information, and make predictions for the future. Moreover, one of the frequent issues of companies is to determine the best visual data storage method. By using on-premises data storage solution, you involve the corporate servers in the process. Firstly, it’s necessary to understand the amount and the type of data, business value of data, and only afterward choose the correct data storage management strategy and data solution for your company.

Summary Definition

Collecting data is a time-consuming process. However, analyzing received information requires more efforts. Scientists use statistical analysis to help managers in making decisions. Today it’s highly popular in politics, social science, medicine, marketing, financial area — almost everywhere! Even if you run your own online store on the Internet, you have to pay attention to the behavior and preferences of your customers and understand your target audience. If you don’t monitor and analyze the information, you’ll hardly develop a proper strategy. It is a crucial step to view new opportunities. Moreover, it helps to predict essential events in similar situations so that you can be prepared for it, save some resources, and minimize your risks. Thanks to visual statistical items, the results of the analysis might be presented in the form of patterns and diagrams. It is convenient for non-technical persons to understand the data.

Statistical data analyst is one of the highest paid jobs today. These specialists have to stay tuned for more news, as their area is quickly developing due to digital information technologies. Only love for analysis and reasoning can keep interested in statistical analysis and as a result — improve our lifestyle.

What’s Next?

You see that statistical analysis is necessary in various fields and requires some skills to make it excellent. Using its methods, you can analyze huge amounts of data, build business predictions, control sales, and more. Don’t miss such an opportunity for your business and order statistical analysis from the experts in this field. Our professional team has a vast experience and the highest standards of quality.