Statistics/Probability and Decision Making:

Decisions making plays a vital role in Business

which eventually outline our lives. Statistics explains how to analysis the

information and evaluation of alternative characteristics in any business

decision making. Statistics uses different models which underlie on computer

programs which makes our life easy to understand the overwhelming flow of data

computer produce.

Statistics helps to:

·

Evaluate and improve the quality of information during

uncertainty

·

Present and explain options

·

Model available alternatives and their

consequences

·

Regulate the smaller decisions required to reach

a larger goal.

Mathematical areas like statistics, probability,

queuing theory, control, optimization, game theory, modeling and operations

research are indispensable for making difficult choices in health, manufacturing,

business, public policy, health, business, manufacturing, finance, law and various

other human endeavors as shown in above SmartArt list.

Inferential

statistics: Inferential

statistics helps to make analysis by taking sample from a large population, as

sample is a small subset the analysis conclusions are unavoidably error prone. Using

inferential statistics we cannot promise that the characteristics of samples accurately

echoes the characteristics of the large amount of population. Thus only

qualified conclusions can be made inside a level of certainty in such case we often

expressed using probability.

Central Tendency: Central

tendency is generally used to compare two normal variables at a point which the

distribution is in balance or centralized. For example, we can compare a scenario

where we need to find out if men earn more than women. Here, we need to compare

their earnings where men and women are normal variable values of gender which

has ratio values. In this case we compare the central tendency of men earnings

with women’s.

Regression analysis: Regression

analysis is the concept used to measure

the degree of correlation between ratio variables where we can use two or more

ratios to analysis the relation between variables. For instance, let us

consider age and wages as two variables, generally one might think that wages might

increase as age increases. But based on hypothesis testing one’s age increases

with experience but not with respect to wages.

Time Series and Forecasting: This method makes forecasting only on the

basis of historical data patterns. The time-series model uses the time as the

main variable to generate the demand. The time series and forecasting method

uses data which are taken in a periodic interval of time like yearly data,

monthly, weekly or any other regular intervals of time. The initial process of

this method is to collect the historical data and use this data pattern the

forecasting or to expect the future measurements. This method is helpful when

the demand is having a consistent data pattern in the previous intervals and is

expected to re-occur in the similar pattern in the future as well.

For instance,

real-estate market of home builders may vary in demand every month in rate. But

by analyzing the previous year’s data, it is evident that the new home sales

are increasing gradually over last few decades. Therefore, we can consider this

as increasing trend in the home building market.

Advantages of Statistics in Business: There are different statistical terms

like average of numbers, mean, median and mode which are simple statistical

tools which are very useful in understanding the various aspects of any

organization’s business. Using these tools, one can get a detailed

understanding of how the company is performing in the past and to know the

actual condition of the company.

Performance Management: Performance evaluation is a key factor in

analyzing any business or organization management. This performance measurement

or performance analysis can be made using the statistical methods by the the

managers or leads of the company by collecting the about the employee’s work,

like how much work is assigned to the employee and the time he/she took to

complete the task and other factors. Considering all these factors the manager

can analyze the performance of the individual and try to get a better

productivity from the employees based on the performance evaluation report. For

instance, if the employee productivity level has decreased by X% on weekends,

then the manager/lead can communicate with the employee one-on-one and set the

expectations on him and try to get the best out of him.

Data Gathering: Statistical data which is collected by the

managers is useful only when the manager is collecting the data in a logical

manner and generates reports in an ethical method. For example, the manager can

collect the performance evaluation details of an employee like how many hours’

employee is working, how much work is assigned etc. Using this data, he can

communicate with the employee and provide a constructive feedback in getting

better productivity. If a product has less sales in the market, by the

collected data he may want to change the amount which is invested

Data Collection: Collecting

data to use in statistics, or summarizing the data, is only an advantage in

business if a manager uses a logical approach and collects and reports data in

an ethical manner. For example, he might use statistics to determine if sales

levels the company achieved for the last few products launched were even close

to projected sales levels. He might decide that the least-performing product

needs extra investment or perhaps the company should shift resources from that product

to a new product.

Research and Development: The company can also use statistical data in

surveying various products available in the market and on analysis of their

product research and development. The

manager can conduct survey on how the product is reached to the target

customers and work accordingly in developing that product. It is also important

to decide how much quality of product is launched at the beginning and what

percent of the target buyers are expected to buy the product. Based on all

these statistical data, the research and development of the product can be

varied.