One of the items that businesses would like to be able to test is whether or not a change they make to their procedures is effective. Remember that when you create a hypothesis and then test it, you have to take into consideration that some variance between what you expect and what you collect as actual data is because of random chance. However, if the difference between what you expect and what you collect is large enough, you can more readily say that the variance is at least in part because of some other thing that you have done, such as a change in procedure.
For this submission, you will watch a video about the Chi-square test. This test looks for variations between expected and actual data and applies a relatively simple mathematical calculation to determine whether you are looking at random chance or if the variance can be attributed to a variable that you are testing for.
Imagine that a company wants to test whether it is a better idea to assign each sales representative to a defined territory or allow him or her to work without a defined territory. The company expects their sales reps to sell the same number of widgets each month, no matter where they work. The company creates a null and alternate hypothesis to test sales from defined territory sales versus open sales.
One of the best ways to test a hypothesis is through a Chi-square test of a null hypothesis. A null hypothesis looks for there to be no relationship between two items. Therefore, the company creates the following null hypothesis to test: There is no relationship between the amount of sales that a representative makes and the type of territory (defined or open) that a representative works in. The alternate hypothesis would be the following: There is a relationship between the kind of sales territory a sale representative has (defined or open) and the amount of sales he or she makes during a month.
Watch this video.
Use the following data to conduct a Chi-square test for each region of the company in the same manner you viewed in the video:
Write an 800–1,000-word essay, utilizing APA formatting, to discuss the following:
Describe why hypothesis testing is important to businesses.
Report your findings from each Chi-square test that you conducted.
Based solely on the Chi-square test, discuss whether the company should accept the null hypothesis in each region or reject it in favor of the alternate hypothesis.
Discuss any other statistical analyses you would want the company to contemplate before deciding if it will go with a defined or open sales strategy.
Describe and discuss at least 1 other business scenario in which you believe Chi-square testing would be helpful to a company.
Bozeman Science. (2011, November 13). Chi-squared test [Video file]. Retrieved from https://www.youtube.com/watch?v=WXPBoFDqNVk
At Solution Essays, we are determined to deliver high-quality papers to our clients at a fair price. To ensure this happens effectively, we have developed 5 beneficial guarantees. This guarantees will ensure you enjoy using our website which is secure and easy to use.
Most companies do not offer a money-back guarantee but with Solution Essays, it’s either a quality paper or your money back. Our customers are assured of high-quality papers and thus there are very rare cases of refund requests due to quality concern.Read more
All our papers are written from scratch and according to your specific paper instructions. This minimizes any chance of plagiarism. The papers are also passed through a plagiarism-detecting software thus ruling out any chance of plagiarism.Read more
We offer free revisions in all orders delivered as long as there is no alteration in the initial order instruction. We will revise your paper until you are fully satisfied with the order delivered to you.Read more
All data on our website is stored as per international data protection rules. This ensures that any personal data you share with us is stored safely. We never share your personal data with third parties without your consent.Read more