Hypothesis testing is vital to test patient outcomes.
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In statistics, we always assume the null hypothesis is true.
In another we present some basic test statistics to evaluate a hypothesis. Hypothesis testing generally uses a test statistic that When describing a single sample without establishing relationships between variables, a is commonly used.
The p-value as or more extreme by chance alone if your null hypothesis is true. This p-value is determined based on the result of your test statistic. Your conclusions about the hypothesis are based on your p-value and your significance level.
Alpha = 0.05. Decision: p-value reject the null hypothesis.
Basically, you reject the null hypothesis when your test value falls into the . There are four main ways you’ll compute test values and either support or reject your null hypothesis. Which method you choose depends mainly on if you have a proportion or a .
the null hypothesis is rejected when it is true b.
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the null hypothesis is not rejected when it is false c.
Based on the evidence, each juror must decide whether they think the person is guilty. The judge will say “guilty beyond reasonable doubt.” Reasonable doubt is what we call a significance level in hypothesis testing.
the research hypothesis is rejected when it is true d.
If the observed outcome, e.g., a sample statistic, is surprising under the assumption that the null hypothesis is true, but more probable if the alternative is true, then this outcome is evidence against H0 and in favor of HA.
the research hypothesis is not rejected when it is false722-1
If you have a , or are asked to find a p-value, follow these instructions to support or reject the null hypothesis. This method works if you are given an and if you are not given an alpha level. If you are given a , just subtract from 1 to get the alpha level. See: .
the result would be unexpected if the null hypothesis were true c.
The significance level (denoted by the Greek letter alpha— ) is generally set at 0.05. The smaller the significance level, the greater the burden of proof needed to reject the null hypothesis, or in other words, to support the alternative hypothesis.