To ensure that your results are valid, consider the following
guidelines when you collect data, perform the analysis, and interpret your
- The data can contain only two categories, such as pass/fail and 1/0
- If you have continuous data, such as length, weight, or temperature,
Randomization test for 1-sample
For more information on data types, go to
types you can analyze with a hypothesis test.
- The sample data should be selected randomly
- 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
in samples of data.
- Each observation should be independent from all other observations
- 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
are dependent and independent samples different?.
- The sample size should not be small
- 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.