What One-sided test is
A one-sided test is a statistical test used to evaluate the differences between two groups or conditions. It is used to determine whether or not the differences between the two groups or conditions are statistically significant.
The steps for a one-sided test are as follows:
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State the null hypothesis and the alternative hypothesis. The null hypothesis states that there is no difference between the two groups or conditions, while the alternative hypothesis states that there is a difference.
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Choose the appropriate test statistic. Depending on the type of data, different test statistics may be used.
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Compute the test statistic. This involves calculating the difference between the two groups or conditions and determining whether or not the difference is statistically significant.
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Calculate the p-value. This is the probability that the difference between the two groups or conditions is due to chance.
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Make a decision. If the p-value is less than the predetermined significance level (usually .05), then the null hypothesis can be rejected and the alternative hypothesis accepted. If the p-value is greater than the predetermined significance level, then the null hypothesis cannot be rejected and the alternative hypothesis cannot be accepted.
Examples
- An experiment where the null hypothesis is tested against a single alternative hypothesis.
- A statistical test to compare two groups on one single measure.
- A test to compare two groups on one outcome measure after adjusting for confounders.
- A test to compare a single group to a population mean or median.
- An analysis of a single metric to detect differences in subgroups.