"It also depends on a lot of other factors — so there's things like if you end up being intubated, that comes with its own risks. " Dr Fox said mortality rates in people needing ICU admission varied a lot between studies. Recovery and future health impacts Dr Fox said while it was early on in the COVID-19 pandemic and more research needed to be done to follow patients over time, most people would make a full recovery. "There's no suggestion from the patients that we've seen that there are any ongoing problems, " he said. "A diagnosis of COVID really makes people very anxious. "I think it's important to try and reassure people that most people who have recovered will be completely well afterwards. " Bridget Wilkins was one of the first people in Australia diagnosed with coronavirus and spent 13 days in hospital before recovering and going home. ( Supplied: Bridget Wilkins) For more severe cases, especially those who spend time in intensive care, recovery is likely to take longer — sometimes weeks or months for a patient to feel "normal".
Statistical tests look for evidence that you can reject the null hypothesis and conclude that your program had an effect. With any statistical test, however, there is always the possibility that you will find a difference between groups when one does not actually exist. This is called a Type I error. Likewise, it is possible that when a difference does exist, the test will not be able to identify it. This type of mistake is called a Type II error. Power refers to the probability that your test will find a statistically significant difference when such a difference actually exists. In other words, power is the probability that you will reject the null hypothesis when you should (and thus avoid a Type II error). It is generally accepted that power should be. 8 or greater; that is, you should have an 80% or greater chance of finding a statistically significant difference when there is one. Increase your sample size to be on the safe side! How do I use power calculations to determine my sample size?
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