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Chapter 9: Inferential Statistics

     


 

Alternative and Null Hypothesis

The purpose of any research is to determine if your theory is true or not based on statistical analysis.  A theory is an educated guess about a relationship but in order for research to be conducted on a theory, it must first be operationalized.  To operationalized a theory, all variables must be defined and the methods of conducting the research must be determined.  Once this is done, the resulting statement about the relationship is called a hypothesis.  The hypothesis is what gets tested in any research study. 

As discussed in chapter one, every experiment has two hypotheses.  The null hypothesis states that there is no change or difference as a result of the independent variable.  In other words, work experience does not result in a difference in grades among college students.  The alternative hypothesis states that there is a change or difference.  When we perform statistics, we are always testing for the null and therefore results of any statistical procedures are always stated in regard to the null hypothesis.  If we find that students with work experience perform at the same level as those without work experience, for example, our results show that there is no difference.  We would therefore accept our null hypothesis.  If we find that one group performs significantly different than the other, we would then reject the null hypothesis, and by definition, accept the alternative.

 

 

 

 

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