Hypothesisinfers to the formal statement that is used to portray theanticipated relationship that exists between two sets of variables,that is, the dependent and the independent variable (Johnson, 2013).The research question is derived from the hypothesis and thenpresented in the form of a question.
Thetwo hypothesis, that is, the null and alternative hypothesis are avalid hypothesis for the research question. The two hypothesis, infact, bring out the relationship that exists between the twovariables, that is the GRE total scores and GPAs in the Master’sprograms in electrical engineering. Focusing on the researchquestion, it is evident that it just the hypothesis that has beenpresented in question form. This affirms the validity of thehypothesis.
Thenull hypothesis for this study is a representation of a theory thathas been put forward. With a view to the argument, the nullhypothesis comes out as true given that it is used as the base forthe argument even though no proof has been made at all.
Thealternative hypothesis for the study refers to the statement in whichthe hypothesis test is going to find out. Comparing the twostatements, it is obvious that null is opposite of alternativehypothesis (Rindskopf, 2016). From the two hypotheses, it is evidentthat the null hypothesis remains to establish the relation to thestatement that is under the test while on the other hand, thealternative hypothesis relates to the statements that are to beaccepted if the null hypothesis is rejected. From the two hypotheses,the conclusion that is reached upon testing will be presented in theform of null hypothesis. From the two, once valid, it is the nullhypothesis either is rejected or fails to reject the alternativehypothesis (Nathoo & Masson, 2015).
Johnson,V. E. (2013). Revised standards for statistical evidence.Proceedingsof the National Academy of Sciences, 110(48),19313-19317.
Nathoo,F. S., & Masson, M. E. (2015). Bayesian alternatives tonull-hypothesis significance testing for repeated-measuresdesigns. Journalof Mathematical Psychology.
Rindskopf,D. M. (2016). Classical and bayesian approaches. WhatIf There Were No Significance Tests?: Classic Edition.