Conclusion How does the test decision relate to the hypothesis, and are your conclusions statistically significant?

The analysis aimed to test whether the salesperson’s average cost per house is above the region’s average in order to validate or refute the claim in the research. The analysis indicates the p-value, which is the test statistic, is less than the level of significance selected for the analysis (p=0.05). Since the decision rule was an upper-tail, we accept the null hypothesis and conclude that the salesperson’s average cost per square foot price is equal to the Pacific region average. This implies that the average cost per square foot of his home sales is not $275, as the advertisement claims. Therefore, it is recommended to review the model used to arrive at the value of $275 and correct the biasedness before publishing the advertisement.

References

Salkind, N. (2015). Excel Statistics: A Quick Guide. Third Edition. SAGE Publications.

Turner, D. P. (2020). Sampling Methods in Research Design. Headache: The Journal of Head and Face Pain, 60(1), 8–12