Linear Correlation of CEO Salary/Quality Control & Statistics - Assignment Example

Linear Correlation The salary of a CEO or Chief Executive Officer is a topic of interest among many. This is so due to the high amount of salary that the typical CEO makes. Many agree that the salary is too high for the level of work and few believe it is even too low. Regardless of one’s beliefs there is believed to be a link between the success of the company and the salary of the CEO. I think most successful companies are able to offer a generous salary to CEO’s as a result of company success.

If a company makes $20 billion dollars a year then a generous salary of $300,000 or so would be adequate. A company that makes only a fraction of the $20 billion would offer a lessened salary. This only makes sense since a company that brings in $300,000 a year would not be able to pay out a $300,000 salary to the CEO. Reasons like this are why the job of a CEO is so important. A CEO is expected to bring a company to the next level and increase profits .When this is done successfully the company and those in share profit.

The CEO then has an incentive as to why they should push the company further and increase sales. If companies with similar market, production, shares etc, where to be placed side by side it is likely that a graph would show a linear similarity. When placed in order with companies that earn lower to higher, CEO salaries would increase along with company earnings. Quality Control Quality control or QC is an important review of a company. When reviewing quality control one is examining different functions of production s within a company.

These different functions are important for a company to be able to carry out specific duties that are needed for the company to strive. Some of the functions reviewed in quality control include the management on projects within the company, checking records and employee relationships. Statistical quality control is similar but has many differences in relation with basic quality control. Statistical quality control uses, “a set of statistical tools used by a quality professional. These statistical tools are broken into three groups that include descriptive statistics, statistical process control, and acceptance sampling.

” (Brue 2002) These specific tools are important in assisting a quality professional in reviewing a company’s production as they relate to statistics. An example of a company that uses statistical quality control is the company Intel. The company has the same set of procedures for production. Each company regardless of location must abide by the same procedures. “Because of the use of statistical quality control, Intel was able to develop a program called exact copy. This program ensures that every product is manufactured the same way.

” (Wiley 2009) The example is a great way to understand how quality control can implement a plan that allows a company to improve production. Improving production is important and using the three basic tools allows the reviewer to gather the necessary information and implement the most successful plan. Works CitedBrue, G. Six Sigma for Managers. New York: McGraw-Hill, 2002.Wiley. "Statistical Quality Control." Wiley. Web. 19 Sept. 2011. .