Week 6 Discussion Responses for Econ and Analytics
Week 6 Discussion Responses – Analysis of Variance - Analytics
Discussion Response 1
By: C,P
ANOVA testing and analysis can be helpful in the business industry. ANOVA to test equality of more than one population means must adhere to the following three assumptions: the populations follow the normal distribution, the populations have equal standard deviations and the populations are independent (Lind, Marchal & Wathen, 2015). F-test is used as the distribution of the test statistic unlike tests used in earlier weeks in our course.
The article I read this week described several ways ANOVA testing could be beneficial to a wide range of industries such as manufacturing, healthcare and the more obvious, business. A manufacturing plant may use ANOVA testing to determine the best materials needed in order to build a specific product for a customer. The company may need to test which metal is the sturdiest to buy. If the cost of three different types of metals, for example, varies significantly in price ANOVA testing can help the firm save money by determining which metal would be the least expensive yet the sturdiest.
Six Sigma is a major sought after certification within the business sectors for my current employer. Many managers in our finance and business departments are often required to obtain Six Sigma certification. What I found interesting is that ANOVA test is used within Six Sigma methodologies within businesses and operations to determine ways to repair processes or make improvements to existing processes. The best managers are those that can make the best decisions for the company and are constantly looking for ways to improve processes. ANOVA testing is an effective tool in determining possible errors, find the best possible resolution and make the appropriate decision with analytical backing supporting those decisions.
Aveta Business Institute. Reasons to use the ANOVA. (2010, July 30). Retrieved from http://www.sixsigmaonline.org/six-sigma-training-certification-information/reasons-to-use-the-anova/
Lind, D. A., Marchal, W. G., & Wathen, S. A. (2015). Statistical techniques in business & economics(16th ed.). New York, NY: McGraw-Hill Education.
Discussion Response 2
By: J,M
Scholars at Miami University conducted a study to explore the connection between negative self-evaluation and mainstream beauty standards. In it, 54 Asian women, 52 Black women, and 64 White women were shown images that demonstrate the Western standard of beauty (thin, White females with blonde hair and blue eyes). They were then asked to rate the photos by completing multiple questionnaires that sought to understand how each woman perceived the images and how each woman perceived themselves both in relation to and apart from the images.
The one-way ANOVA test was used to test quite a few measures. For example, they use the test to find that Black women found the mainstream standard to be the least favorable (that is, they gave the images a lesser rating on the "beautiful" scale". White women rated it most favorably and Asian women fell between the two. The one-way ANOVA test also showed that Black women, who did not find the mainstream standards to be personally applicable, they rated their own personal self-attractiveness higher than Asian and White women. The tests also revealed that Asian women were more likely to value conforming to mainstream ideals.
Chin, P. E. (et. al) (2003). Do racial minorities respond in the same way to mainstream beauty standards? Social comaprison processes in Asian, Black and White women. Retrieved from: http://web.a.ebscohost.com.libweb.ben.edu/ehost/pdfviewer/pdfviewer?vid=1&sid=553f1b87-99e6-4141-bce9-32491dbf6865%40sessionmgr4006
