A hypothesis is a technique that is used to investigate and express a relationship that is expected to between two separate variables. According to Copley et al 66, when a hypothesis is applied, the reason behind putting it into use is to examine whether there is data supporting the hypothesis. Steps taken while stating any hypothesis include using the theoretical framework to derive at the hypotheses, designating dependent and independent form of variables in the applicable hypotheses and stating of the hypotheses that is to be applied.
An null hypotheses (Ho), is one that is put in place and is subject to be refuted, nullified or rejected. Such a hypotheses is rejected where a researcher is of the opinion of supporting an alternative hypothesis (Judith, 45). A null hypothesis is put in place and assumed to be correct until a hypotheses test is carried out, where statistical evidence may show that the null hypotheses was wrong. This happens when the person carrying out the research has enough reason to believe that, the null hypothesis is not supported by the data available.
A null hypotheses puts forward a common theory, or that which may be believed to be true. A researcher may also put forward such a hypotheses to be used as an argument basis. the hypotheses is left open to be approved by the statistical results. For instance, a researcher may make a statement that a certain personal trait is not likely to influence them to commit crimes. An alternative hypothesis is also put in place so that when the null hypothesis is rejected, then the alternative one is taken. Special attention is however given to the null hypothesis becase it closely relates to the question which is being tested.
The alternative hypotheses (H1), is a statement that is subject to proof or disapproval, once a statistical test is carried out on a hypotheses. Where a null hypotheses is established, the alternative hypotheses is set up so that, it may be applied in case the null hypotheses is rejected. For example, in a research study, the H1 statement may be that, most sexual crimes are on the increase due to the influence of alcohol intoxication, the alternative statement would be that drug addiction is the factor that has contributed to most of the sexual offenses.
Once the test has been carried out, the final result is arrived at where the conclusion is given relating to the null hypotheses. It can for instance be stated that, Ho was rejected and that H1 was favored or that, H0 was not rejected. A null hypotheses is not necessarily true because it has not been rejected, it may have been approved due to that fact that there may be no other good evidence to disapprove it.
A simple hypotheses is one that is used to state the exact distribution of a population by doing a thorough statistical collection of data. In a simple hypotheses, the distribution parameters value are specified even before the samples are drawn (Judith, 47). A composite hypotheses on the other hand, may be distinguished from the simple hypotheses due to the fact that, the composite hypotheses does not completely specify the distribution of the population. In the composite hypotheses various parameters may not be known and may be estimated by the use of sample observations. Composite hypotheses helps one to identify the specific area of the population in which data is collected and a researcher can easily identify his area of interest. The two hypotheses, the simple and composite, may be used to carry out a statistical test that may help to approve or disapprove a null hypotheses.
Copley, Walt. Criminal Justice research Methods CJ408 Grantham Arts & Sciences Series. 3rd Edition.
Grantham University, Kansa City, Mo USA. Prentice Hall, 2006. 65-69
Judith, D. Applied Longitudinal Data Analysis: Modeling Change and Event Occurrence. Published by Oxford University Press US, 2003. 43-47
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