The Effective Use and Importance of Hypothesis in Management

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The 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 researchers for it to be proven correct. Thus, hypotheses are to be tested just prior to proving them in the case of some claims underlying various researchers.There are many ways on how to test a hypothesis. Statistically, a hypothesis can be viewed as the 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).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 was 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 to these figures but the bottom line is that all of them explained how to classify information to finally come up with a general conclusion.