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This is a question consultants are frequently asked because the client wants to make sure their results are going to be “statistically significant”.  It is a complex theory without a simple answer.  We have all heard of the term statistically significant and we all know it’s a “good thing”, but what does it mean?

nbsp;head Spring nbsp;shoes nbsp;mouth apricot nbsp;sleeve nbsp;small nbsp;shallow nbsp;female nbsp;square shoes nbsp;footwomen's nbsp;leather nbsp;heel nbsp;shoe Statistical significance is the probability your results happened by pure chance and therefore may not truly represent your population.  In other words, significance is the probability of error.  If you were to survey every single person in your population, you would not have to worry about error because you would be 100% confident that your results are accurate, therefore making your significance level zero.  In statistics, the terms significance and confidence are related.  In percentage terms, confidence = 100% - significance.  A significance level of 5% is the same as a confidence level of 95%.  Confidence level is what most people think about when referring to statistical significance because it is much clearer to state that you are 95% confident of a finding rather than reporting a significance level of 5%.

nbsp;head nbsp;shoe nbsp;mouth Spring nbsp;female nbsp;small apricot nbsp;square nbsp;heel nbsp;shoes nbsp;shallow nbsp;sleeve nbsp;footwomen's shoes nbsp;leather Realistically though you can never be 100% confident in your results.  Because you typically only survey a portion of your population, you have to accept there is a probability of error.  Therefore, you have to ask yourself “how much error am I willing to accept?”  This depends on the type of study you are conducting.  If you are testing the strength of a bridge or the side effect of a new drug (i.e., circumstances in which a “bad” result can have tragic consequences), you’d probably want less than .001% error; but if your data is less precarious, such as comparing satisfaction ratings or average incomes, then 5% error is a commonly accepted amount.  By asking yourself that question, you can establish an appropriate significance level (.001% or 5%) and corresponding confidence level (99.999% or 95%).

Understanding significance/confidence is one of the first steps in interpreting statistical results.  Referring back to the original question, statistically significant results imply your results have an acceptable amount of error.  Since there will always be some level of error in the results of a typical survey, the goal is to minimize its probability of occurrence with proper survey methodology and statistical analysis.   A consultant can help you with this based on the topic of your study and available resources.

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