Statistics

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Statistical Comparative Analysis for EnergyX

Ahmad Abu Hammour

Department of IT, Southern States University

IT 531: Data Analytics

Dr. Tem E. Bugarin

May 29, 2022

Statistical Comparative Analysis for EnergyX

EnergyX is a mock energy drinks company, and it produces more than 100 million cans every year. EnergyX has ten factories across the United States. Recently, a new CEO took place, and he realized that the company was not doing well. Accordingly, he asked his team to provide him with the issues preventing the factory from producing more energy drinks and reaching more consumers.

After several meetings and much brainstorming, the team proposed three significant issues facing the business and several strategies to solve the issues. The three main issues are the low production volume, the overweight of the energy drink cans, and the high QA failures. Finally, the team provided the CEO with the possible solutions, and they suggested performing three hypothesis tests to measure the efficiency of each solution. Comment by Tem Bugarin: Okay at this point you provided a very credible job in identifying a problem statement for the energy X drink company that will enable you to go into continuing this paper.

This paper will discuss the company's issues and the possibility of applying the suggested solutions according to the results of the hypothesis tests. Also, it will discuss how to perform the three hypothesis tests and the eight steps of analysis. Comment by Tem Bugarin: This last paragraph the great introductory into your main theme of your paper.

Performing Hypothesis Tests to Solve the Company's Three Main Issues

The new CEO of EnergyX is trying to improve the overall quality of the products and the services provided. To do so, EnergyX's team addressed three significant issues facing the company. This section of the paper will discuss these three issues, how to solve them, and how to apply the hypothesis testing to predict the results of the new applied strategies (solutions). The three main issues are The low production volume, The energy drinks cans overweight, and The high QA failures. Comment by Tem Bugarin: Research Questions

Low Production Volume

EnergyX's team realized that the production volume was less than the average. Accordingly, they proposed five suggestions to the CEO to increase the production volume. The five suggestions are building a new factory, hiring more workers, increasing the hours of operation, installing a new production line, or buying new robot machines.

The CEO and the team decided to start installing the new production line as a solution to increase the production volume. Below is a spreadsheet showing the number of produced cans for each month before installing the new production line.

Figure 1

The Number of Produced Cans for Two Years Period

Note. The figure above is a spreadsheet showing the number of produced cans for two years and the average number for five months.

Figure 1 shows the number of produced cans over the past two years. Also, it shows the average number of produced cans for five months. However, after installing the new production line and testing the results for five months, they found out that the new average of the produced cans for five months is $150K while the old average is $124K.

The new numbers are good, but they are no definite evidence that the new production line will increase the production volume. So, the CEO asked his team to perform a hypothesis test to determine if there is a statistically significant difference between the old and the new average number of produced cans for five months period. Comment by Tem Bugarin: Comment by Tem Bugarin: This last sentence looks like feels like a research question that doubles as a hypothesis test..

Hypothesis Test 1

According to (Rawat, 2021), "Hypothesis testing is the act of testing a hypothesis or a supposition with a statistical parameter. Analysts implement hypothesis testing to test if a hypothesis is plausible or not." The hypothesis test consists of eight steps, where the significance level is 0.05, and the standard deviation is 10. This test aims to determine if there is a statistically significant difference between the old and the new average number of produced cans for five months period.

As shown below in figure 2, the team applied the eight steps of the hypothesis testing, and they ended up with a conclusion that installing the new production line has made a statistically significant difference. Accordingly, they recommended using the new production line to increase the production volume.

The team solved the first issue facing the company by applying a new strategy and testing it for five months using the one-tail hypothesis test. The hypothesis contains eight steps that use the Z formula and a significance level of 0.05.

Figure 2 Comment by Tem Bugarin: Figure 2 and hypothesis test one should be centered secondly you state your know an alternate hypothesis being associated with the number 124 however you need to state that in your preceding paragraph. Essentially you're asking if increasing the hours of operation or installing a new production line will increase the production volume. This little tidbit needs to be addressed in the write up prior to doing your hypothesis test.

Hypothesis Test 1

Note. The figure above shows the eight steps of hypothesis testing used to test the strategy of installing a new production line.

The Overweight of the Energy Drink Cans

The second issue facing the EnergyX company is the difference in the cans' weight as

the workers in the factory realized that the weight of the energy drink cans is different from the standard weight. The standard weight of the company's energy drink cans is 21 ounces. However, for the last 50000 cans, they found out that the new average weight is 21.6.

Hypothesis Test 2

The CEO asked his team to determine if the new weight differed from the standard 21 ounces. The team decided to perform the eight steps of hypothesis testing for 36 days at a 0.05 significance level and a standard deviation of 0.5. Comment by Tem Bugarin: These two opening paragraphs that describe the overweight of the energy drink cans and hypothesis test to our is really a good statement about what they hypothesis test two is all about. You need to do the same thing with hypothesis test number one.

Figure 3 Comment by Tem Bugarin: Figure 3 needs to be centered

Hypothesis Test 2

Note. The figure above shows the eight steps of hypothesis testing used to test the production machines.

The team used the eight steps of hypothesis testing to determine if the current production machines are filling more ounces in the cans. The hypothesis testing showed that the new machines served more energy drinks and caused losses to the company. Accordingly, the team recommended replacing all the old machines with new ones to cut the losses for the company.

Decreasing the QA Failures

The company's third issue is the high-quality assurance failures due to the used logistics company. According to (Kenton, 2022), "Logistics refers to the overall process of managing how resources are acquired, stored, and transported to their final destination." The CEO asked his team to provide solutions to decrease the QA failures. The team found out that the currently used logistics company is the issue as it does not perform the required tasks on time.

The team informed the CEO that the current logistics company is causing the company a $10K of QA failures due to their inaccurate timings. However, they decided to switch to a new logistics company to determine if using the new company would make a statistically significant difference.

Hypothesis Test 3

The team tested the new logistics company for 60 days and found that the QA failures dropped from $10K to $7.8K. Accordingly, they decided to perform the eight steps of hypothesis testing to determine if using the new logistics company makes a statistically significant difference. The team will perform the hypothesis testing at a significance level of 0.05 and a standard deviation of two for 60 days.

Figure 4 Comment by Tem Bugarin: figured four needs to be centered now the hypothesis statement within the Excel spreadsheet has a number 10 I can only assume that new equals 10 represents QA failures dropping from 10K to 7.8 K the 10 represents the 10K. This is okay. It was a little confusing and can be clarified just a little.

Hypothesis Test 3

Note. The figure above shows the eight steps of hypothesis testing used to determine if using the new logistics company will decrease the QA failures.

As shown in figure 4, switching to the new logistics company made a statistically significant difference in the QA failures. Accordingly, the team recommended using the new logistics company as it decreased the value of QA failures.

Conclusion

The new CEO of EnergyX company realized that the company was not doing well. Accordingly, he asked his team to find the main issues facing the company and propose possible solutions to increase the company's overall revenue. The team did multiple meetings and informed the CEO of the company's three key issues. The three significant issues are the low production volume, the overweight of the energy drink cans, and the high QA failures. Furthermore, the team proposed possible solutions to make the company perform better. However, these solutions are not guaranteed to be efficient. Accordingly, the CEO asked the team to perform hypothesis tests for the three suggested solutions.

The hypothesis tests aim to predict whether the results make a statistically significant difference or not or determine if the new results are different from the old ones. The first hypothesis test was performed to determine whether or not installing a new production line would increase the company's production volume. The results showed that it would increase the production volume. Accordingly, the team recommended using the new production line.

The second hypothesis test was to determine whether or not the current robot machines are filling more ounces of energy drink in the cans. However, the results showed that the machines malfunction and should be replaced. Finally, the third hypothesis test was to determine if switching to a new logistics company will decrease the QA failures or not. The results showed that switching to the new logistics company made a statistically significant difference. Accordingly, switching to a new logistics company will decrease the QA failures and increase the revenue.

References

Kenton, W. (2022, March 22). Logistics. Retrieved from Investopedia: https://www.investopedia.com/terms/l/logistics.asp Rawat, S. (2021, July 22). What is Hypothesis Testing? Types and Methods. Retrieved from Analytic Steps: https://www.analyticssteps.com/blogs/what-hypothesis-testing-types-and-methods