Final answer:
The hypothesis "Patient characteristics will predict hospital readmission after discharge" is an alternative hypothesis, as it makes a specific claim regarding the effect of patient characteristics on readmission rates, contrary to a null hypothesis which would state there is no such effect. It would typically be tested with a two-tailed test in statistical analysis.
Step-by-step explanation:
The statement "Patient characteristics will predict hospital readmission after discharge" is an example of an alternative hypothesis. This is because it is a specific claim stating that there is an effect or a difference to be observed, as opposed to the null hypothesis, which would assert that there is no effect or no significant difference.
The null hypothesis (H0) is typically a statement of no effect or no difference and is the hypothesis that researchers aim to test against. The alternative hypothesis (Ha) expresses the opposite, indicating some effect or relationship. If we turn this statement into a hypothesis for statistical testing, H0 might state "Patient characteristics do not predict hospital readmission after discharge", while Ha would be "Patient characteristics predict hospital readmission after discharge".
Determining if the test is right-tailed, left-tailed, or two-tailed depends on the specifics of the hypothesis being tested. However, the provided hypothesis does not specify a direction for the prediction, so we might typically consider this a two-tailed test.