What Is Business Statistics?A collection of procedures and techniques that are used to convert data into meaningful information in a business environment.The most common description of statistics is that it’s the process of analyzing data — number crunching, in a sense. But statistics is not just about analyzing the data.

It’s about the whole process of using the scientific method to answer questions and make decisions. That process involves designing studies, collecting good data, describing the data with numbers and graphs, analyzing the data, and then making conclusions.

Business Statistics is the science of ‘good' decision making in the face of uncertainty and is used in many disciplines, such as financial analysis, econometrics, auditing, production and operations, and marketing research. It provides knowledge and skills to interpret and use statistical techniques in a variety of business applications. A typical Business Statistics course is intended for business majors, and covers statistical study, descriptive statistics (collection, description, analysis, and summary of data), probability, and the binomial and normal distributions, test of hypotheses and confidence intervals, linear regression, and correlation.

Importance of Statistics in Modern Business Environment With fast moving technologies, advanced communication network, rapid changes in consumer behaviour, varied expectations of variety of consumers and new market openings, modern managers have difficult task of making quick and appropriate decisions. Therefor e there is need for them to depend more upon quantitative techniques like mathematical models statistics, operation research and econometrics. These techniques push back the domain of ignorance and rule of thumb and enlightens them with new horizon of thought process.

Branches of Statistics1. Descriptive Statistics2. Inferential Statistics

Descriptive Statistics:The procedures and techniques that comprise business statistics include those specially designed to describe data, such as charts, graphs, and numerical measures.

ExampleDuring the 1990s and early 2000s, many major changes occurredin the financial services industry. Numerous banks merged. Money flowed into the stock market at rates far surpassing anything the U.S. economy had previously witnessed. The international financial world fluctuated greatly. All these developments have spurred the need for more financial analysts who can critically evaluate and explain financial data to customers. At Crown Investments, a senior analyst is preparing to present data to upper management on the 100 fastest growing companies on the Hong Kong Stock Exchange.

In addition to preparing appropriate graphs, the analyst will compute important numerical measures. One of the most basic and most useful measures in business statistics is onewith which you are already familiar: the arithmetic mean or average.

The total profit for the 100 companiesis $3,193.60, but profits are given in millions of dollars, so the total profit amount is actually $3,193,600,000. The average is found by dividing this total by the number of companies:

Average = = $31,936,000 Million Dollars

Another Example

Inferential StatisticsHow do television networks determine which programs people prefer to watch? How does the network that carries the FIFA cup, know how many people watched the game? Advertisers pay for television ads based on the audience level, so these numbers are important; millions of dollars are at stake. Clearly, the networks don’t check with everyone in the country. Instead, they use statistical inference procedures to come up with this information. There are two primary categories of statistical inference procedures : estimation and hypothesis testing. These procedures are closely related but serve very differentpurposes.

TV RATINGS: The television networks cannot know for sure how many people watched last year’s Super Bowl. They cannot possibly ask everyone what he or she saw that day on television. Instead, the networks rely on organizations such as Nielsen Media Research to supply program ratings. For example, Nielsen (www.nielsenmedia.com) surveys peoplefrom only a small number of homes across the country asking what shows they watched, and then uses the data from the survey to estimate the number of viewers per show for the entire population.Advertisers and television networks enter into contracts in which price per ad is based on a certain minimum viewership. If Nielsen Media Research estimate an audience smaller than this minimum, then a network must refund some money to its advertisers.

Hypothesis Testing Television advertising is full of product claims. For example, we might hear that “Goodyear tires will last at least 60,000 miles” or that “more doctors recommend Bayer Aspirin than any other brand.” Other claims might include statements like “General Electric light bulbs last longer than any other brand” or “customers prefer McDonald’s over Burger King.” Are these just idle boasts, or are they based on actual data?

Populations, Samples, and Sampling Techniques

PopulationThe set of all objects or individuals of interest orthe measurements obtained from all objects orindividuals of interest.

SampleA subset of the population.

A population includes measurements made on all the items of interest to the data gatherer. In our example, the McDonald’s manager would define the population as the waiting time for all 566 cars. The list of these cars, possibly by license number, forms the frame. If she examines the entire population, she is taking a census. But suppose 566 cars are too many to track. The McDonald’s manager could instead select a subset of these cars, called a sample.

The manager could use the sample results to make inferences about the population. For example, she might calculate the average waiting time for the sample of cars and then use that to conclude what the average waiting time is for the population.

Parameters and StatisticsDescriptive numerical measures, such as an average or a proportion, that are computed from an entire population are called parameters. Correspondingmeasures for a sample are called statistics. Suppose in the previous example the McDonald’smanager timed every car that arrived at the drive-thru on a particular day and calculated theaverage. This population average waiting time would be a parameter. However, if she selecteda sample of cars from the population, the average waiting time for the sampled cars would bea statistic.