Today’s businesses are not just run by intuition. In fact, modern derivatives of firms, organizations, and corporations use a variety of tools in order to ensure that they would earn profit both in the short run and in the long run. In the past, before the proliferation of the various devices that are used in information communication technology, the success of a business largely depends on chance and the management methods that are made by its proprietors, managers, and even the actual employees. Today, however, businesses employ many other tools in order to ensure future profits and returns for the capital they funnel in to their ventures (Farr & Timm, 1994).
One method that is deeply valuable and important in today’s business process is the business research process. The business research process allows for organizations to understand many aspects of the operations of the firm. The business research process is essential in understanding the organization and how it operates, produces, and profits in different time frames. The business research process may also be able to help you be understanding of the market and industry in which the business is competing.
Also, business research becomes essential especially in the aspect of differentiating goods
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In this process, perhaps one of the most essential aspects and tools is data. Data, however, in its raw form, is almost of no use to any individual, manager, or firm. In order to be able to process data and understand the various relationships they have another, the main tool that must be use these statistics. Statistics allow for not only the analysis of data, as well as the explaining of the various interpretations of the data that have been gathered, but advanced statistics — the kind of statistics that is used in modern business, could even be able to predict various outcomes.
Just an example of this is the linear regression analysis — using statistics in order to create a best fitting line, of course considering a term of error, so that an impotent change in one variable may be able to predict the outcome of another variable (Burton, Carrol, & Wall, 2002).
Businesses, therefore, integrated with statistics, and business research, is a science of decision making by managers through the use of the manipulation and analysis, as well as the interpretation, of data. It is used in the business research process such as financial research, accounting research, auditing, and even operations research. Other specialized applications of the business research process using statistics is marketing research and predicting behavior of individuals by integrating behavioral economics and other such disciplines of the social science in order to predict reactions of consumers to the goods and services — pricing, quantity, and many other variables — so that a firm may be able to make an accurate and informed decisions.
In fact, statistics in the business research process is a kind of applied statistics (Lind, Marchal, & Wathen, 2005). In fact, only recently, in 2007, a book entitled “Super Crunchers” was published and was pushed to the best-selling list of business books. The book basically discussed how statistical analysis such as linear regression is used by businesses worldwide in order large corporations such as Wal-Mart to make informed decisions. As a result, according to the book, the businesses who made use of the business research process using applied statistics adding able to significantly increase their productivity levels and eventually the profit of firms (Ayres, 2008).
A requirement that has been instructed to us is to find a business statistics related article and evaluate the information according to specific guidelines that have been given. The article that we have chosen is a report published by Rockstars Publishing in 2008 accredited under the popular freelancing blog FreelanceSwitch. It is basically a report that had been done by collecting various information from all over the Internet from various freelancing disciplines such as web designers, programmers, project managers, and so forth. The report is basically a statistical, violation of the reports of these surveys and provides various descriptive statistics as to the state of freelancers — their geographical distribution, the kind of work they do, financial details, and even measures of happiness and welfare towards the end.
In the question of whether or not the information was adequate, we could perhaps comment that it was enough to capture the specific markets which it originally wanted to describe. In looking at the report, it included demographics, details about the life of freelancers and the distribution of the kinds of jobs, work-related issues like financing, credit debt, salaries, average scatters of hours of work per week by freelancers all over the world, and even the kinds of projects these freelancers receive.
However, a comment that we would like to add in looking at this article is that perhaps it should have added other statistical reports that have been made regarding non-freelancing careers so that they are very be a cross comparison of the various statistics that they have made. Because the report was composed of descriptive statistics, having a side-by-side comparison with the industry it is trying to compare it with — the industry of regular employment — could have made the reader more informed and had produced a better picture of the freelancer life.
In the question of are the statistics misleading in the context of the topic, we would say that it was not. Misleading statistics are often used by those gathering information and trying to market a certain good or service. The report we are discussing, however, is not trying to market a specific industry. In fact, it does not even say that freelancers have a comparative advantage over regular employees because there were sections where in freelancers wanted to shift back to their previous employment benefits.
The next question was whether or not the statistics was used as a piece of numerical information or was it used for the decision-making process. The report, in fact, could be able to capture both. However, in the aspect of numerical information, it is the main purpose of the article to deliver to its readers the actual statistics and data gathered by the survey and present them in graphical form so that the readers are not boggled down by tables and numbers, but rather descriptive statistics that have already been summarized.
There was, however, no kind of predictive model or interpretation other than that of descriptive statistics. With respect to decision-making, on the other hand, the article itself, since it was a compilation of data, did not have a decision-making Bremer. However, perhaps it may be able to help its readers to make better and informed decisions in the industry they are working and poor will be working in the future.
The statistics in the survey results were compiled in a summarized and informative manner. In fact, the layout of the article itself was easy to read because of the typography and the design of the survey results. Perhaps we should not be surprised by this because the publishers of the said survey are a group of graphic designers — freelancing graphic designers obviously — who wanted to share to the world as well as to know themselves the state of the freelancing business, especially freelancers who spend a large time Internet — for that is where the survey had been made in the 1st place.
The last requirement that is asked in this paper is to make analysis and drove our own observations about the information presented. According to the article that we have reviewed, although they did not specify because, as we have already claimed earlier, the article did not have any interpretations but rather only presented the data that had been gathered from the survey, freelancers — specifically freelance web designers and programmers, are steadily increasing in numbers.
In the past, in order for you to succeed in a graphic design, web design, or programming career, you must belong to a company that is already reputable with respect to the output that they produce in that circuit and specific industry. An inference could be made that the freelancing lifestyle and the freelancing career is beginning to get more popular these days. An inference, again, that we may make to support this is that the information communication technology available today — such as high speed Internet, mobile phones, and the like — allow for individuals to work in whichever locations they please.
An eventual result of this is that many of them work from home and without a specific company. In fact, in our analysis of the statistics, we see that the income of freelancers are steadily rising, implying that the industry is booming and that we could expect more freelance web designers, programmers, and graphic artists to enter the market in the future rather than entering formal cubicle-based offices.
Another observation that we could make when we look at the data in the article is that there is a certain kind of happiness that is attached in working from home. However, this happiness is balance by the cost of the various benefits that are forgone by freelancers which they could have from companies such as package medical insurance, vacation benefits, allowances, and the like.
Although this is not explicitly stated in the article and in the data that were presented to descriptive statistics, we could at least see that many of the factors regarding the decision of workers to shift to the freelancing movement is a balance between the freedom of working in a fluid environment and a self dictated rate of work — not to mention the cost of commutes and the stress of the working environment — and the various benefits of companies.
There are many other statistics and information that could be found in the article, and these are just some of the highlights that we have considered essential in answering the various question that had been required from us.
Ayres, I. (2008). Super Crunchers (p. 260).
Burton, G., Carrol, G., & Wall, S. (2002). Quantitative methods for business and economics (p. 480).
Farr, R. C., & Timm, P. R. (1994). Business research (p. 112).
Lind, D. A., Marchal, W. G., & Wathen, S. A. (2005). Statistical Techniques in Business & Economics (p. 800).
Ricketts, M. (2003). The Economics of Business Enterprise (p. 592).