Business Statistics Are Vital to the Livelihood Term Paper

Pages: 6 (1554 words)  ·  Bibliography Sources: ≈ 11  ·  File: .docx  ·  Level: College Senior  ·  Topic: Business

Business statistics are vital to the livelihood of an organization. No organization in modern society, whether large or small is likely to succeed without using some business statistics every day. Business statistics are used in many ways. Statistics for example are often used as part of decision making processes and part of continuous improvement programs (Hillmer, 1996). This is perhaps the most beneficial use statistics have to offer. Statistics provide tangible data regarding an organizations productivity, problem areas, inventory and more. Statistics basically provide a snapshot of an organizations well being.

Managers within a corporation need statistical tools to problem solve, predict cost benefit ratios, decide important issues and determine the course of action that will result in the best outcome for a company (Hillmer, 1996). Statistics can also help executives decide whether business units are maintaining reasonable budgets, decide whether overhead is reasonable and decide what products and services should be used or dropped in the future (Hillmer, 1996).

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Use of statistics in business has many benefits. It can shorten the time it takes for managers to come to a decision regarding a problem. Decision makers can calculate cost benefit ratios to determine what solutions are most likely to benefit the company and which alternatives are most likely to influence a company in a negative manner. Statistics also allow a birds eye view of the company's progress toward its goals and objectives. Statistical applications can tell executives how productive a company is and how well it is doing compared with the competition. Statistical applications can also be used to predict future areas of growth or future problem areas that need to be addressed by executives in the company.

Part 2 - Mean, Median Mode & Standard Deviation Dayton OH Temperatures

Term Paper on Business Statistics Are Vital to the Livelihood Assignment

This study examined the mean, median, mode and standard deviation for Dayton Ohio Temperatures during February, specifically the temperatures in late February. To collect this information historical data was gathered for mid day temperatures in Dayton, OH on February 26 for the last 20 years. The mean was calculated by determining the average sum of scores, thus all temperatures divided by twenty or the number of temperatures collected. The median equates to the middle value of all data selected, or the temperature in the middle of all other temperatures. The Mode equates to the most frequent temperature, which was 34 degrees Fahrenheit. The standard deviation is calculated using the deviation method from the mean square, a summary of which includes calculating the mean to determine N, where N. equals the number of scores. Standard deviation simply measures the way data is spread compared to the mean value of data. The mean is subtracted from each of the numbers given and the result squared to get the standard deviation.

The data suggests that the temperatures in Dayton during February remain relatively constant, with seemingly random fluctuations that are roughly 10 degrees higher or lower than the median temperature. A majority of the temperatures collected fall between 30 and 40 degrees Fahrenheit with little fluctuation. There are no warming trends noted with the exception of temperatures between 1997 and 1998, which remain roughly 10 or more degrees higher than the average temperature. This could be attributed again to random fluctuations in temperature.

Temperature Mid Day

Sum

Mean - Average Scores

Median Temperature

Mode - Most Frequent

Standard Deviation

Part 3 - Permutations and Combinations

Permutations and combinations can be used in the decision making process in businesses today. They can help a manager compare differences and similarities between two or more choices (In fact within a business environment permutations and combinations are one of the most "widely used statistical methods" for decision makers) (Arsham, 1994). They can enable statistical modeling and help managers determine if a plan is likely to result in positive or negative outcomes. Combinations allow a decision maker to select the best course of action from an un-ordered group of objects, problems or situations.

A permutation enables more sequenced decision making based from an ordered selection of choices. A fundamental aspect of business is trade where an organization provides something in exchange for something else, sometimes referred to as "Barter Economics" (Arsham, 1994). A company can use permutations and combinations to determine how many alternatives exist with regard to a particular situation, such as how much risk is involved working with one corporation vs. another or one supplier vs. another (Arsham, 1994). A company can calculate the probability of risk and if that risk is too high the relationships might result in two dissatisfied parties. Permutations may also be used to calculate trading ratios (Arsham, 1994).

Part 4 - Probability

Probability can be used in business to help determine the likelihood that certain future events will occur (Arsham, 1994). It can also help executives base decisions on the most probable positive outcome given multiple scenarios to choose from. Probability analysis is a widely used business tool for evaluating scenarios in a business environment.

Probability is the act of determining the likelihood that given phenomena will occur without relying solely on random guessing. Probability thus helps managers and other business executives determine the best course of action given multiple alternatives (Arsham, 1994). Probability can also be used to determine the likelihood that adverse events will happen, such as the likelihood that certain threats to corporate assets will be realized within a designated time frame.

Corporations can use probability projections to determine where they should invest money to protect assets in this case based on the most probable threats or likelihood that a catastrophic event might occur within an organization. A company can also use probability to decide what course of action, like building a new product or offering a new service is most likely to generate the highest profits at the least cost. While probability is not an exact science it can reduce an organization's capacity for error and improve the chances that a decision made will benefit the company to the best extent possible. Probability can even be used when hiring an employee to determine what the likelihood is one candidate will do better or serve the organizations needs vs. another.

Part 5 - Probability Distributions

Probability distributions enable better problem solving within an organization. Statistical devices like probability distributions can help businessmen make sound business decisions by providing better market intelligence which in turn allows executives to utilize their resources in a manner most likely to "produce premium customer value" (Waller, Dabholkar & Gentry, 2000). Probability distributions can for example help business executives determine the most optimal conditions under which successful implementation of organizational directives are likely to occur (Waller, Dabholkar & Gentry, 2000).

Statistical devices like this can also help executives better analyze the industry and competitive conditions under which an organization is operating, better understand an organizations resources and capabilities and better customize organizational systems to meet the needs of a dynamic customer base (Waller, Dabholkar & Gentry, 2000). Probability distribution is particularly helpful for determining optimal production distribution and enabling organizations to decide how many products should be produced and inventoried at one given time vs. another (Waller, Dabholkar & Gentry, 2000). Rigorous analysis of probability distribution enables organizations to streamline supply chain strategies and postponement strategies to focus on "superior customer value" and other key factors to an organizations success in their industry (Waller, Dabholkar & Gentry, 2000).

Part 6 - Normal Distribution is the most common distribution used by business executives to analyze data and trends within an organization. Normal distribution s beneficial in part because it lends itself to relatively few errors, and those errors that do arise are generally considered so small they can easily be overlooked or deemed acceptable (ICMBA, 2002).

Random variation is typically associated with normal distribution, which describes "the most commonly observed probability distribution" (ICMBA, 2002).… [END OF PREVIEW] . . . READ MORE

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