Null Hypothesis and Statistical Significance: John and Sons

Introduction to the Null Hypothesis

The null hypothesis often states the opposite of what an experimenter is attempting to prove (Lane, 2009). The experimenter wants or expects to disprove the null hypothesis, which is expressed as H0. Understanding what the null hypothesis claims — namely, that there is no difference or no effect — is the essential first step in designing any statistical test.

Formulating the Hypotheses for John and Sons

Consider the case of John and Sons Company, which wants to open a new factory overseas to take advantage of lower wages abroad but is concerned about the potential quality implications of this move. John and Sons has had quality-control problems in the past with its overseas operations. In this context, the null hypothesis (H0) would be: "There is no statistically significant difference in the number of defects in a batch of the product manufactured in country X versus a batch manufactured in the United States." This phrasing captures the core meaning of the term null hypothesis — that there is no difference.

The alternative hypothesis (H1) would be that there is a statistically significant difference in the number of defects found in batches made in country X versus those made in the United States. As Quick MBA notes, "this alternative hypothesis states that the relationship observed between the variables cannot be explained by chance alone" (Hypothesis testing, 2009).