0
Statistics is a useful tool for the leadership ( Managers, Vice Presidents, CEO , Owner of any business etc ) to make decisions.
Example
Organizations made a bar chart to see on what weekdays their employees take maximum leaves. They found that most the employees took these unscheduled leaves on a Friday or Monday or both.
This is a simple statistical study. Lets say if you have 20,000 people working with you. Doing this study manually without statistics would take a very long time and possibility of error will also be very high. With statistics it takes only a few second to make a bar chart on Microsoft Excel.
Just one glance at the chart and you see the bar on Friday or Monday or both three times higher than other weekdays. Like they say a picture is worth a thousand words.
This information can help the management to take proper measures to reduce the number of unscheduled leaves on Fridays and Mondays.
Still curious? Ask our experts.
Chat with our AI personalities
Judy
Professor
DevinAdd your answer:
Earn +20 pts
What is the application of statistics in business management?
Statistics is used in Business Management to tell the trend of the sale of certain goods and services. It is used to predict the various factors that affect trade.
How do you use descriptive statistics in business management?
Stan nyoko
How statistics is useful in business management?
Statistics help businesses determine the best approach to attracting customers. Managers study demographics and learn how to market their products to customers.
What is the importance of statistics in project management?
Stastics produce reliable information relative to project management as opposed to myths and rules of thumb that are developed more randomly and with less reliability. .,
Roles of a inferential statistics in statistics?
Statistics is a general field of numeric quantities and what they represent. For example, a statistic may be inferential or descriptive. Inferential statistics are special kinds of statistics that use sampling distributions to make inferences from a sample to a population of interest (hopefully that the sample represents). The inferences are more or less valid based on how well one meets the assumptions of a statistical method/model and how robust a statistical method is with respect to violations of an assumption.
