The Effective Use and Importance of Hypothesis in Management - Assignment Example

The Effective Use and Importance of Hypothesis in Management Reading through the article of Bryant (1998), various implications can be figured out. These are the implications of the article for both the practice of management and for research on that practice. In this paper, the following implications from the article of Bryant (1998) are discussed. 1. The effective use and importance of hypothesis 2. The use of statistics and significance of numbers 3. The logic in research 4. The use of data 5. The association or relationship of things being tested The effective use and importance of hypothesis Let us discuss first the effective use and importance of hypothesis in research and management. Hypothesis from experiences in research is the fundamental basis of the kind of information that are wanted to be found out or tested. Hypothesis is the underlying concept that will guide the entire research process just prior to decision making process in the field of management. Hypothesis such as presented by Bryant (1998) about the claim that CEOs who play a good game of golf also run high-performing companies is subject for various tests and more researches for it to be proven correct. Thus, hypotheses are to be tested just prior to prove them in the case of some claims underlying various researches. There are many ways on how to test a hypothesis. Statistically, a hypothesis can be viewed as subject for testing the validity or truth of the statement. If the researcher failed to prove the hypothesis, then he or she has also failed to provide sufficient evidence to prove the validity of a null hypothesis (Reeves & Brewer, 1979). Casualty and Inference 3 The use of statistics and significance of numbers Statistics is one of the best tools used to analyze and obtain information from a given data or set of information. Statistics consists of numbers and these are used to define and form concrete information. In the article of Bryant (1998), the importance of statistics was justified when specific average handicap index of golfers were calculated to obtain and deduce specific information from it. The given information when combined can be used effectively especially in inferential statistics. Inferential statistics uses numbers and data or data set to obtain conclusive information. However, it cannot be denied that the information that will be obtained is dependent on the raw data. There are many ways to draw inferences from the raw data but many of them are heading to wrong direction (Knowledge @ Wharton, 2008). In the article of Bryant (1998), the inference is dependent on the given numbers explaining average handicap index of golfers. There can be many things related about these figures but the bottom line is that all of them explained how to classify information to finally come up with a general conclusion. This simply means that there is a clustering of information and then finally observation for specific trend that can give rise to one whole specific label of the raw data. The good thing about being specific of certain hypothesis is the organization of information that inevitably can pave way to better understanding of the human mind. This means that in order for a certain claim to be accepted, information that proves something must be organized and logically presented. The logic in both management and research is very important. Casualty and Inference 4 The logic in research A logical presentation of information was clearly presented in the article of Bryant that which at some point was able to promote understanding of newly discovered information. The information consisted numbers with underlying meaning that can also help justify conclusive evidence. This implies that at the basic unit of research, primary justifiable information shall be obtained and shall be analyzed for the justification of the entire research process. The justification of the entire research process is a mere proof of following the logic in research. This is one of the notable processes involved in the research output of Bryant. His article showed how numbers speak for themselves which at some point; the bottom line is to organize information in a logical manner. Another important observation from the article of Bryant is the presentation of idea through numbers which carry certain meaning, value, category or classification. From this alone, logical presentation of information was made possible and the convenience in absorbing it made easy. This is to imply that a logical research can be much more appealing due to the fact that it is not hard to comprehend and there can be more related concept in line with the human understanding. This is perhaps the reason why Bryant’s article continues to get attention. The use of data Raw data are very important in any research or management concerning information from the real world. The use of data in particular can give rise to a more effective evaluation of a phenomenon. Casualty and Inference 5 Bryant’s article is a living proof how the use of data can give rise to obtaining important and significant conclusion. This means that in order to obtain a much more significant conclusion, data must be complete and sufficiently covered the entire information to be tested. Data is the basic unit in every research considering that conclusion at the later part depends on what they are and how they are being processed. Bryant’s article suggests that it is important to make use of data and utilize them properly for a more effective attainment of result. After all, nothing can be inferred without data. This is also another way of saying that the data must be sufficient for the result to be reliable in the same way that more significant conclusion can be deduced from them. The article of Bryant presented data as to how the entire information of the research was presented. It can be noted that a sufficient number of data must be very important to obtain significant result. However, as presented in the article of Bryant (1998), only few of the CEO would like to talk about their golf games. This implies that the data of Bryant might be lacking and not entirely representing the entire population of those CEO who played golf. The association or relationship of things being tested It can be noted that Bryant (1998) presented hypothesis. He claims that CEOs who play a good game of golf also run high-performing companies. In this hypothesis, two things or statements are claimed highly associated or related to each other. 1. Golf performance of CEO 2. Performance of the CEO’s company The above statements are found closely associated to each other based on the test and research conducted. Casualty and Inference 6 However, before their relationship was found out, the statement “ CEOs who play a good game of golf also run high-performing companies” stands first as a hypothesis ready to be tested for its validity. Its validity was dependent on the actual research process and the number of information at hand. Furthermore, it is important to look at primary information through observation just to come up with a specific hypothesis for testing. It is therefore appropriate to find out first some probable relationship of things through a specific observation just prior to collection of data and making of more detailed conclusion. Establishing valid conclusion requires more than just the knowledge of the subject matter. It requires more detailed information on other related aspects. For instance, to find out for the reliability of result from the article of Bryant, it is important to understand the research process itself which starts at formulating hypothesis and will eventually go through data analysis. Data analysis can be so challenging. Aside from formulating hypothesis, data analysis maintains a well-processed raw data to finally come up with a good output. In the case of research, a good output implies better findings or results. Casualty and Inference 7 References Bryant, A. (1998). Investing it: Duffers Need Not Apply. Retrieved May 19, 2009, from The New York Times Web site: http://www.nytimes.com/1998/05/31/business/investing-it-duffers-need-not-apply.html Reeves, C. A. &, Brewer, J. K. (1979). Hypothesis Testing and Proof by Contradiction: An Analogy. Retrieved May 22, 2009, from Testing Statistics Web site: http://ts.rsscse.org.uk/bts/reeves/text.html Knowledge @ Wharton (2008). The use and misuse of statistics: How and Why Numbers are so Manipulated. Retrieved May 22, 2009, from Knowledge @ Wharton Web site: http://knowledge.wharton.upenn.edu/article.cfm?articleid=1928 Read More