When is a standard deviation too high?
For normally distributed characteristics, the rule of thumb is that around 68 percent of all response values are within one standard deviation above and below the mean. Around 95 percent of all values are within two standard deviations. Larger deviations are referred to as outliers.
When is a confidence interval significant?
If a confidence interval does not contain the value of the “zero effect”, a “statistically significant” result can be assumed. A distinction would then have to be made as to whether the confidence interval for the relative risk is completely below 1 (= protective effect) or completely above it (= increased risk).
When is the null hypothesis rejected?
The null hypothesis can only be rejected if the p-value is less than the significance level.
What does the null hypothesis say?
The assumption about the “population” to be tested as part of a “hypothesis test” is called a null hypothesis. The null hypothesis is often not the assumption that is actually of interest, the so-called working hypothesis, but the assumption that you want to refute.
What is null hypothesis and what is alternative hypothesis?
In statistics, the null hypothesis is an assumption that is to be tested using a hypothesis test. The null hypothesis states that there is no difference or connection between two tested data. The alternative hypothesis (H1) represents the opposite assumption.
What is h0 and h1?
The hypothesis is denoted by H0, null hypothesis. The opposite of this, i.e. the “counter-hypothesis” to it, is denoted by H1, alternative hypothesis. So in the real (unknown) world either H0 or H1 is always true.
How to test hypotheses?
Procedure for hypothesis testsYou set up your hypotheses (null and alternative hypotheses).You choose the test that fits your question.You determine the significance level α.You collect your data.Use this data to calculate a summary indicator, the test variable (or test statistic)
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