null and alternative hypotheses are different for each set of data. typically the hypothesis that is accepted and being tested against is the null hypothesis (denoted by Hsub0.) it may be in the form of data collected by a previous study. the alternate hypothesis (denoted by Hsub1) is an observation of the sample statistics that directly contests the null hypothesis. The two hypothesis are mutually exclusive, if one is true than the other must be false. null and alternate hypothesis may be stated as following.
Hsub0 = a
Hsub1 %26gt; a
running a t-test will result in a p-value attained from a calculator or a t-score chart. if the p-value is smaller than alpha, the level of significance, Hsub0 is rejected. If it is greater than or equal to alpha, Hsub0 is failed to be rejected. note that your conclusion should always be in terms of Hsub0.|||Null hypothesis is the default, alternative hypothesis is what you are testing for to disprove the null hypothesis.
eg. Ford Motors says the average that their cars go s 35 mph (null) but I think they actually go more than 35 mph.
Null: Mean = 35mph
Alternative: Mean %26gt; 35mph
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