To ensure that your results are valid, consider the following guidelines when you collect data, perform the analysis, and interpret your results. 
 
 
 
 
- The populations of each sample must have the same shape and spread 
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If the populations have different shapes or spreads, use 2-Sample t without pooling variances.  
- The data do not need to be normally distributed 
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However, if you have more than 15 observations in each sample or your data aren't severely skewed, use 2-Sample t because the test has more power.  
- The sample data should be selected randomly 
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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.  
- Each observation should be independent from all other observations  
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The independence of observations is determined by whether one observation provides information about another observation, as follows: 
  
-  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. If your observations are dependent, your results may not be valid.