To ensure that your results are valid, consider the following guidelines when you collect data, perform the analysis, and interpret your results.
- The data should include at least one categorical factor
- For more information on factors, go to Factors and factor levels.
- The response variable should be continuous
- If a response variable is categorical, you cannot use the equal variances test because a valid standard deviation does not exist. The response column must contain numeric values, such as weights.
- The sample sizes should be greater than 20
- If some of the groups have fewer than 20 samples, the multiple comparisons p-value might not be valid.
- Each observation should be independent from all other observations
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If your observations are dependent, your results might not be valid. Consider the following points to determine whether your observations are independent:
- If an observation provides no information about the value of another observation, the observations are independent.
- If an observation provides information about another observation, the observations are dependent.
- The sample data should be selected randomly
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Random samples are used to make generalizations, or inferences, about a population. If your data were not collected randomly, your results might not represent the population.
- Collect data using best practices
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To ensure that your results are valid, consider the following guidelines:
- Make certain that the data represent the population of interest.
- Collect enough data to provide the necessary precision.
- Measure variables as accurately and precisely as possible.
- Record the data in the order it is collected.
