To ensure that your results are valid, consider the following guidelines when you collect data, perform the analysis, and interpret your results.
If you have continuous data, such as length, weight, or temperature, use Randomization Test for 1-Sample Mean. For more information on data types, go to Data types you can analyze with a hypothesis test.
In statistics, random samples are used to make generalizations, or inferences, about a population. If your data are not collected randomly, your results may not represent the population. For more information, go to Randomness in samples of data.
For observations to be independent, the probability of a particular outcome does not depend on any previous outcome. For example, if you flip a coin twice and record whether heads or tails is face up, the outcome of the second flip does not depend on the outcome of the first flip. If your observations are not independent, your results may not be valid. For more information, go to What is an independent trial?.
If your sample size is small, the resampling results may be unreliable. To ensure that your results are valid, collect a medium to large sample. An adequate sample size depends on the characteristics of the data. Use the histogram to determine whether your sample size is large enough.