Data plays an important role in business operations. By carrying out statistical analysis, starting from collecting, processing, to analyzing data, companies are able to make concrete reports regarding the conditions of business development.
The achievement of the invested effort can be illustrated from the results of the statistical analysis. In addition, the results of statistical analysis can also be used as a reference in taking strategic business steps in the future. This article will discuss a brief understanding of statistical analysis, types, and benefits that can be obtained.
A little information about the differences between statistics and statistics before discussing further about the meaning of statistical analysis. Statistics is a collection of data, numbers, or information. Meanwhile, statistics is a science that studies the collection, processing, and analysis of data and numbers. The results of the statistical analysis can be in the form of certain information that is used to make decisions.
The purpose of statistical analysis itself is to identify patterns or trends and eliminate bias in business decision making objectively. Descriptions such as the products that consumers buy the most, employee performance, to variations in sales performance, can be answered by conducting statistical analysis.
What are the types of statistical analysis? There are at least seven kinds of statistical analysis that are often used. The use of this type of statistical analysis needs to be adjusted to the goals to be achieved. Within business, the implementation of certain types of statistical analysis can also be influenced by the business model and target customers.
Types of descriptive statistical analysis include summary charts, graphs, and tables that describe sets of data or numbers to make them easier to understand. In this way, large data sets can be simplified. The results of the descriptive statistical analysis, including the mode, median and average, as well as the range, variance and standard deviation.
It should be remembered that this descriptive statistical analysis cannot conclude an analysis in general. Therefore, a more detailed analysis is needed to complete the description of the results of the descriptive analysis.
While descriptive statistical analysis is based on an overall picture, inferential statistical analysis is performed by drawing conclusions based on data representing a population. With inferential statistical analysis, one can validate a conclusion of information or data from the population to be studied.
In accordance with its name, statistical association analysis is used to predict a trend or pattern by identifying certain relationships of several data variables. For example, statistical association analysis analyzes variables that occur more frequently. In implementing statistical association analysis, special software is needed to be able to carry out complex systematic calculations from the available set of variables.
Causal analysis uses data to determine cause-and-effect relationships from a context. This type of statistical analysis can be applied to business purposes, such as quality assurance, customer satisfaction and retention, and other matters that are still related to cause and effect.
As the name implies, predictive statistical analysis is implemented to predict future events and behavior. This type of statistical analysis requires machine learning to be able to process data sets into new information. This analysis is influenced by probabilistic techniques such as data mining, predictive modeling, artificial intelligence (AI), to model simulation.
Similar to predictive statistical analysis, this type of statistical analysis also utilizes the sophistication of machine learning in processing data. Prescriptive statistical analysis is carried out by optimizing the application of mathematical and computational sciences to produce several choices. This type of analysis generally begins with the results of descriptive and predictive statistical analysis.
Considered a type of complex statistical analysis, Exploratory Data Analysis (EDA) is able to answer the relationship between samples in a population, validate assumptions, and test hypotheses. This type of statistical analysis is used to analyze patterns and trends in large data sets.
One of the benefits of statistical analysis, which helps in making business decisions objectively. In addition, good statistical analysis results can reduce the business risk of unfavorable decisions or strategies.
Companies can analyze data and costs more accurately by using statistical analysis. In running a business, it certainly requires a lot of operational costs. This limited cost needs to be allocated to each need proportionally, based on the need to get the maximum benefit.
Accurate and objective market analysis is needed to develop business potential that can still be maximized. For example, opening a shop branch needs to consider the location, the condition of the surrounding environment, to the traffic of vehicles and the local community.
Statistical analysis can help business owners to be able to carry out market analysis based on data and facts. Another example of market analysis that can be generated from statistical analysis, namely data regarding the most sales locations, types of products or services with the highest value, to marketing strategies that have succeeded in attracting consumers. Having such market analysis allows for increased efficiency in every aspect of sales and marketing.
Statistical analysis is at the heart of optimal business development. Decision making or objective business strategy can increase profit opportunities for the company. For example, descriptive statistical analysis carried out using A/B testing (A/B testing) provides a clearer picture of the choice of products or services that are aligned with the needs of clients or consumers.
Another example of the benefits of statistical analysis, namely making decisions to release the latest product or feature on a company page or website. By collecting in-depth information such as the duration of visits, the number of visitors, to the increase or decrease in sales necessary before and after the implementation of the new feature or product is released. The results obtained need to be evaluated further, whether they should be maintained or redeveloped according to consumer needs.
That is information about the seven kinds of statistical analysis complete with their benefits for more optimal business development.
Data plays an important role in business operations. By carrying out statistical analysis, starting from collecting, processing, to analyzing data, companies are able to make concrete reports regarding the conditions of business development.
The achievement of the invested effort can be illustrated from the results of the statistical analysis. In addition, the results of statistical analysis can also be used as a reference in taking strategic business steps in the future. This article will discuss a brief understanding of statistical analysis, types, and benefits that can be obtained.
A little information about the differences between statistics and statistics before discussing further about the meaning of statistical analysis. Statistics is a collection of data, numbers, or information. Meanwhile, statistics is a science that studies the collection, processing, and analysis of data and numbers. The results of the statistical analysis can be in the form of certain information that is used to make decisions.
The purpose of statistical analysis itself is to identify patterns or trends and eliminate bias in business decision making objectively. Descriptions such as the products that consumers buy the most, employee performance, to variations in sales performance, can be answered by conducting statistical analysis.
What are the types of statistical analysis? There are at least seven kinds of statistical analysis that are often used. The use of this type of statistical analysis needs to be adjusted to the goals to be achieved. Within business, the implementation of certain types of statistical analysis can also be influenced by the business model and target customers.
Types of descriptive statistical analysis include summary charts, graphs, and tables that describe sets of data or numbers to make them easier to understand. In this way, large data sets can be simplified. The results of the descriptive statistical analysis, including the mode, median and average, as well as the range, variance and standard deviation.
It should be remembered that this descriptive statistical analysis cannot conclude an analysis in general. Therefore, a more detailed analysis is needed to complete the description of the results of the descriptive analysis.
While descriptive statistical analysis is based on an overall picture, inferential statistical analysis is performed by drawing conclusions based on data representing a population. With inferential statistical analysis, one can validate a conclusion of information or data from the population to be studied.
In accordance with its name, statistical association analysis is used to predict a trend or pattern by identifying certain relationships of several data variables. For example, statistical association analysis analyzes variables that occur more frequently. In implementing statistical association analysis, special software is needed to be able to carry out complex systematic calculations from the available set of variables.
Causal analysis uses data to determine cause-and-effect relationships from a context. This type of statistical analysis can be applied to business purposes, such as quality assurance, customer satisfaction and retention, and other matters that are still related to cause and effect.
As the name implies, predictive statistical analysis is implemented to predict future events and behavior. This type of statistical analysis requires machine learning to be able to process data sets into new information. This analysis is influenced by probabilistic techniques such as data mining, predictive modeling, artificial intelligence (AI), to model simulation.
Similar to predictive statistical analysis, this type of statistical analysis also utilizes the sophistication of machine learning in processing data. Prescriptive statistical analysis is carried out by optimizing the application of mathematical and computational sciences to produce several choices. This type of analysis generally begins with the results of descriptive and predictive statistical analysis.
Considered a type of complex statistical analysis, Exploratory Data Analysis (EDA) is able to answer the relationship between samples in a population, validate assumptions, and test hypotheses. This type of statistical analysis is used to analyze patterns and trends in large data sets.
One of the benefits of statistical analysis, which helps in making business decisions objectively. In addition, good statistical analysis results can reduce the business risk of unfavorable decisions or strategies.
Companies can analyze data and costs more accurately by using statistical analysis. In running a business, it certainly requires a lot of operational costs. This limited cost needs to be allocated to each need proportionally, based on the need to get the maximum benefit.
Accurate and objective market analysis is needed to develop business potential that can still be maximized. For example, opening a shop branch needs to consider the location, the condition of the surrounding environment, to the traffic of vehicles and the local community.
Statistical analysis can help business owners to be able to carry out market analysis based on data and facts. Another example of market analysis that can be generated from statistical analysis, namely data regarding the most sales locations, types of products or services with the highest value, to marketing strategies that have succeeded in attracting consumers. Having such market analysis allows for increased efficiency in every aspect of sales and marketing.
Statistical analysis is at the heart of optimal business development. Decision making or objective business strategy can increase profit opportunities for the company. For example, descriptive statistical analysis carried out using A/B testing (A/B testing) provides a clearer picture of the choice of products or services that are aligned with the needs of clients or consumers.
Another example of the benefits of statistical analysis, namely making decisions to release the latest product or feature on a company page or website. By collecting in-depth information such as the duration of visits, the number of visitors, to the increase or decrease in sales necessary before and after the implementation of the new feature or product is released. The results obtained need to be evaluated further, whether they should be maintained or redeveloped according to consumer needs.
That is information about the seven kinds of statistical analysis complete with their benefits for more optimal business development.
