Statistics/Probability business, manufacturing, finance, law and various

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.

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Statistics helps to:

Evaluate and improve the quality of information during

Present and explain options

Model available alternatives and their

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.


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




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