Hypothesis Of A Hypothesis Test

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Hypothesis testing is very essential in statistical analysis. It is quite imperative to state both a null hypothesis and an alternative hypothesis when conducting a hypothesis test because the hypotheses are mutually exclusive and if one statement is true then the other is proven as false. According to Mirabella (2011, p. 4-1) states that, “When we have a theory about a parameter (the average is…,the proportion is….,etc), we can test that theory via a hypothesis test.” Therefore, that is what we have used to determine if the average age of Whatsamatta U MBA students is less than 45. We have to conduct a one sample hypothesis test to prove if we can accept or reject the null hypothesis. In order to determine what decision rule, which is the statement that tells under which condition to reject the null hypothesis, to propose we must first determine if we are instituting a upper-tailed, lower-tailed, or two-tailed test. There are many steps used when initiating a hypothesis test. First and foremost it is vital to specify the null and alternative hypothesis, next we have to determine a significance level that is tolerable such as 0.05 which is your tolerance for error, and last we have to calculate the statistic that is comparable to the parameters set by the null hypothesis.

Additionally, when utilizing hypothesis testing, we are attempting to determine whether or not to accept or reject the null hypothesis. Furthermore, we have to determine if there is enough
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