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Hypothesis testing involves drawing inferences about two contrasting propositions (hypotheses) relating to the value of a population parameter, such as a mean, proportion, standard deviation, or variance. (Evans, 2013)  In hypothesis data they like to use sample data to analyze and come up with the population and etc.  It really would depend on what is being analyze.
Conducting a hypothesis test can be very challenging and informative.  We have to first determine is the situation or even due to chance or is there a cause.  Then, we have to examine the cause to prevent it from happening again.  Then we need to streamline everything that happen from beginning to.  In hypothesis testing there is a lot of methods that can be used; such as traditional and p value.    P value is almost identical to the traditional.  The beginning steps is exactly the same.  This is what make the difference between right and wrong statistics. 
Parametric information is more accessible.  For example, if you are doing a story if it is a parametic hypothesis testing this means the information is there and you can review, but nonpararmetric no information will be available.  Parametric is more in your face and up front whereas non parametric you have to work a little hard to get the resolution that you would like.  Parametric is considered to be more powerful and acceptable than others. 
Hypothesis testing is a way of coming up with a solution using data to get a