APPLICATION OF STATISTICS AND ITS METHODS IN BUSINESS

 

APPLICATION OF STATISTICS AND ITS METHODS IN BUSINESS

 

Statistics is a particularly useful branch of mathematics that is not only studied theoretically but one that is used by researchers in many fields to organize analysis and summarized data. Statistical methods and analyses are often used to communicate research findings and to support hypotheses and give reliability to conclusions.

 

APPLICATION OF STATISTICS IN BUSINESS

Statistics play an important role in business. A successful businessman must be very quick and accurate in all situations and take decisions properly based on situations. Businessmen can plan production according to the taste of customers. When all the activities of a business are run based on statistical methods, the quality of the products can be checked more efficiently by using statistical methods. So all the activities of the businessman are based on statistical information. Based on the trend of the statistics, a businessman can make the correct decisions about the location of the business and the different products to be manufactured.

1)Accounting:

Public accounting firms use statistical sampling procedures when conducting audits for their clients. For instance, suppose an accounting firm wants to determine whether the number of accounts receivable shown on a client’s balance sheet fairly represents the actual amount of accounts receivable. Usually, the large number of individual accounts receivable makes reviewing and validating every account too time-consuming and expensive. As a common practice in such situations, the audit staff selects a subset of the accounts called a sample. After reviewing the accuracy of the sampled accounts, the auditors draw a conclusion as to whether the accounts receivable amount shown on the client’s balance sheet is acceptable

2)Finance:

The financial analysis uses a variety of statistical information to guide their investment recommendations. By comparing the Information for an individual stock with information about the stock market averages, a financial analyst can begin to draw conclusions as to whether an individual stock is over-or underpriced.

3)Marketing:

Electronic scanners at retail checkout counters collect data for a variety of marketing research applications. For example, data suppliers and Information purchase point-of-sale scanner data from grocery stores, process the data, and then well statistical summaries of the data to manufacturers. Manufacturers spend hundreds of thousands of dollars per product category to obtain scanner statistics and promotional activity statistics to gain a better understanding of the relationship between promotional activities and sales.

4)Production:

Today’s emphasis on quality makes quality control an important application of statistics in production. A variety of statistical quality control charts are used to monitor the output of a production process. In particular, a v-bar chart can be used to monitor the average output. Suppose, for example, that a machine fills containers with 12 ounces of a soft drink. Periodically, a production worker selects a sample of containers and computes the average number of ounces in

the sample. This average, or the value, is plotted on a v-bar chart. A plotted value above the chart’s supper control limit indicates overfilling, and a plotted value below the chart’s lower control limit indicates underfilling. The process is termed “in control” and allowed to continue as long as the plotted v-bar values fall between the chart’s upper and lower control limits. Properly interpreted, av-bar chart can help determine when adjustments are accessory to correct a production process.

5)Economics:

Economists frequently provide forecasts about the future of the economy or some aspect of it. They use a variety of statistical information in making such forecasts. For example, in forecasting inflation rates that economists use statistical information on such indicators as the Producer Price Index, the unemployment rate, and manufacturing capacity utilization. These statistical indicators are often entered into computerized forecasting models that predict inflation rates.

 

STATISTICAL METHODS USED IN BUSINESS

MEAN-

ARITHMETIC MEAN-Mean is one of the most important measures that help particularly in location depicting the central location for a particular set of data. It has widespread application in business like-to know the no. of units produced on a large assembly line per day, no of orders that have been received on a daily basis. It is also used to know the average production and costs, per capital income exports, consumption, current prices, etc

GEOMETRIC MEAN-It’s only for sets of positive real numbers. In business, GM is helpful in constructing index numbers. The averages of proportions, percentages as well as compound rates can be derived by using GM. The growth of population is measured in it as population rises in GP.

HARMONIC MEAN-The harmonic mean is the lowest mean and is used to calculate. This is applied to speed, time, values that are given in quantities, rate, and prices are involved.

MODE-

Mode is the value that appears the most number of times in a particular dataset. It’s a very important tool of analysis in statistics to know what happens most often. While analyzing prices, most of the sales occur at a particular price or possibly at a reduced, sale price. While there are different sales at different prices, hardly any customers will have paid an average or a mean price. Thus, they’re relative of lesser significance while setting price in terms of what the customers have paid.

MEDIAN-

Median is a positional measure of central tendency. The median salary gives a value close to the average salary commonly paid, without taking the extreme values into consideration. There are mainly used in qualitative cases like honesty, intelligence, ability, etc. These are also suitable for the problems of distribution of income, wealth, investment, etc.

INDEX NUMBERS-

This technique is used to compare the differences between the present year product values and previous year product values.

CORRELATION-

Correlation is another most useful statistical method. These belong to the most common useful statistical tools to compare the effects and performances of variables. Correlation analysis is applied to independent factors: If X is increased, What will Y do. In Regression analysis Changes in X result in Changes in Y but Changes in Y do not result in changes in X. To discover whether there is a relationship between variables. To find out the direction of the relationship-whether it is positive negative or zero. This measure varies from 0 to 1 and 0 to-1. The test statistic correlation coefficient measures the strength of the relationship between the two variables.

 Ex: 1) Find the relationship between the net profit and cash flow 2) What is the relationship between salespersons and number of sales.

STANDARD DEVIATION-

Standard deviation is a measure of how to spread out a data set is. It’s used in a huge number of applications.

  • In finance, standard deviations of price data are frequently used as a measure of volatility.
  • It is often used by investors to measure the risk of a stock or a stock portfolio.
  • In manufacturing, it is used as a way of quality control.
  • In polls and surveys, it can be used to measure the level of confidence in our results.

For example, if you look at salaries for everyone in a particular company, from a student intern to the CEO, the SD may be very large. If one only observes student interns, the SD is smaller since individuals within this particular group have fewer variable salaries.

RANGE-

It is widely used for weather forecasting by the meteorological departments. It is also used in statistical quality control. Range is a good indicator to measure the fluctuations in price change like that of studying the variations in the price of shares and debentures and other related matters. Following is the procedure of calculating range:

Range= value of the highest observation (H) – value of the lowest observation (L) or Range = H – L

 

CONCLUSION

A business needs to analyze, interpret and compare its performance. Statistical tool plays a role-play important role in business research.

 

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