Free hypothesis essay example

Once a study question has been identified, it is essential to formulate a hypothesis. A research question is a broad statement that includes all the variables that are to be considered in the study, while the hypothesis is a statement that details the specific relationship expected to be observed while examining the variables in a specific study.
While formulating a hypothesis, a researcher has to consider the values that form the basis of a good hypothesis. Good hypothesis must be able to identify the dependent and independent variables; it has to specify the nature of the relationship that exists between the dependent and the independent variable. A good hypothesis is parsimonious (simple) as it is always advisable to have short and concise hypothesis than a long one. A good hypothesis does not contain references to specific measures, as it does not refer to specific statistical procedures that the researcher will use in the analysis of the variables. A good hypothesis describes the population that the researcher will study and has to be falsifiable and testable. It is always prudent to have several hypotheses than having one that is complex, the recommended number being six hypothesises or less per study. A study that contain more than six hypothesises is most likely to be time consuming when writing the discussion part of the study, as it is hard to write a discussion with many hypothesises to consider. It is also hard to keep the intended participants interested, and uninterested participants do not take the responses as important, which may compromise the quality of the answers to the question.
The two most common types of hypothesises are the null hypothesis and the alternative hypothesis. The null hypothesis is a statement indicates the value of the parameters of the population that the study will cover. It states that the value of the population parameter is equal to the claimed value and is always denoted as equality. a hypothesis test is necessitated to confirm if the null hypothesis is true of false. The null hypothesis is an appropriate hypothesis that meets the criterion of a good hypothesis. It is because the null hypothesis is testable and simple to understand. Null hypothesises, however, are faced by two types o errors that are the Type 1 and Type 2 errors. A type 1 error occurs when the null hypothesis that is to be accepted is rejected and a type 2 error occurs when the null hypothesis that is to be rejected is accepted. An alternative hypothesis is usually developed when the null hypothesis is rejected. An alternative hypothesis is denoted using signs like ‘ greater than,’ ‘ lesser than’ or ‘ equal to.’ Alternative hypothesises are easy to understand but are hard to compute as various hypothesis tests have to be carried out to determine whether the population parameters are appropriate or not. Thus in my opinion the alternative hypothesis is not an appropriate hypothesis on the basis of complexities in computing.