Statistics in Business

Statistics:

The quantitative presentation of numerical data is known as statistics. Any object, subject, activity, or phenomenon may be the information in this case. In addition to being a science of estimates and probabilities, statistics may also be described as the collection of facts. For instance, summary statistics give a general picture of a dataset, such the average exam score. The average, however, does not necessarily provide the full picture; for instance, if the average score is 70, it could just reflect the fact that 50 percent of the students earned 100s and the other 50 percent received 40s. In contrast to if every student in the class had received 70, which demonstrates consistency, this would display a different picture.

Characteristics of statistics:

• Facts are collected into statistics. One number is not statistical data.
• Numerous factors affect statistics.Sales of a product, for instance, are influenced by factors like price and quality.
• A methodical approach must be taken when gathering statistical data. For the statistics to be trusted, the data shouldn't be gathered randomly.
• The statistical data must be quite precise. Statistics ought to be based on precise data that has been gathered.

Business Statistics:

Business statistics is the study of data that supports the formulation of uncertain business decisions using certain quantifiable and numerical values. Data must be gathered, categorized, summarized, organized, analyzed, and interpreted. Business statistics' fundamental goal is to draw conclusions about specific population traits, whether the population consists of individuals, objects, or collections of data. Numerous prosperous businesses make substantial use of statistics. Businesses employ statistical methods to assess their performance, determine which processes are effective and which require improvement.

Importance of statistics in business:

There are three major functions of statistical methods in any business enterprise. These are as follows:

• The planning of operations: This relates to either unique projects or the ongoing operations of a company over a predetermined time frame.
• The setting up of standards: This is related to factors like the size of the workforce, the amount of sales, the establishment of quality standards for manufactured goods, standards for daily output, and more.
• The function of control: The control function entails comparing the actual production to the target production that was previously defined. If the production does not meet the desired level, it offers alternatives to ensure that this shortcoming does not recur in the future.

Although these three tasks appear to have diverse purposes, in reality, they are extremely closely tied to one another.

Various authors hold varying opinions regarding the value of statistics in business. Croxton and Cowden state that project planning, budgetary planning and management, quality control, inventory planning and control, marketing, production, and personnel administration are some of the business applications of statistics. Additionally, they have identified specific fields where statistics is more applicable. Irwing W. Burr, a different author, listed a few business-related areas where statistics can be useful, including: customer needs and market research, development, design, and specification, buying, production, inspection, packaging, and shipping, sales and complaints, inventory and maintenance, costs, management control, industrial engineering, and research.

Applications of statistics in business:

There are many applications of statistics in business. Some of them are:

• Statistics for market research:
  One of the most popular uses of statistics in business is market research. It seeks to pinpoint the discrepancy between consumer wants and the goods and services that are being offered to them on the market. There are two major strategies. The qualitative method addresses the attitude of the consumer and their perspective, as opposed to the quantitative approach, which deals with the client's profile, behavior, and preferences. The representativeness of the data or information gathered is essential to the validity of the survey results, regardless of the strategy used. It will be necessary to use a variety of statistical techniques to create a representative sample because it is typically difficult to survey the full target population, which can be very big. We need statistics in market search rather than using common knowledge because the customers and their wants are dynamic. Customers can like some product this year and choose a different product next year.
• Statistics for forecasting:
  The art of forecasting involves making predictions about the future based on current or past events. A well-developed mathematical framework for business forecasting has been made possible by theories in multiple regression and time series analysis. In reality, forecasting relies on a mathematical model made up of a series of complex regression equations that have been refined over time. Various statistical methods, such as regressions, variance, skewness, and range, are used in forecasting. Sales forecasting is a common application of forecasting in business. There are two fundamental types of forecasting models: quantitative (data-focused) and qualitative (focuses on users).
• Statistics for quality assurance:
  During the decision-making process, the accuracy and quality of the data must be known. A quality control mechanism is employed in this process to guarantee a predetermined degree of quality for the goods and services the company provides. This is only conceivable since it was generated by a reliable analytical system that was in a statistically controlled state. Establishing a quality assurance program that includes system quality control and quality assessment of the generated data is necessary. Various tests, including the t-test and f-test, are applied to ensure this.

Limitations of statistics in Business:

Firm statistics are an effective tool for running any kind of business. There are some restrictions on how it can be used, though. As follows:

• Difficulty of understanding: People have trouble understanding things and thinking logically.
• Small sample size: It is challenging to make accurate predictions or forecasts when the sample size is small.
• Frequency: Frequency is frequently utilized in statistics tests, although this may not accurately reflect the questions we are posing.
• Outcome Bias: When employing statistics in business, managers frequently experience outcome bias.

Reference:

• Kunda, Surinder. An Introduciton to business statistics. n.d.
• bayt.com/en/specialties/q/8634/define-business-statistics/
• smallbusiness.chron.com/limitations-business-statistics-58608.html