PCA-734-m21

4

Week 8

Practical Connection Assignment

DSRT-734-M21 Inferential Statistics in Decision Making

University of the Cumberlands

Doug Bennett

06/18/2021

Inferential statistics

Statistics courses are highly valued worldwide because they provide graduates with a common language and framework for describing businesses and project resources through statistical knowledge. They Statistical knowledge also provide graduates with a versatile range of skills for predicting the future, making them capable of managing change and achieving project goals in any industry or business. A good statistics course will can equip you one (Use third-person voice in APA style writing) with the skills to prioritize competing interests at each project stage, allowing you one to maintain high standards, best practices, and high levels of customer satisfaction by forecasting future changes, particularly in customer preferences, using statistical knowledge gained in class (Trafimow & MacDonald, 2017). This course will provide you with the specialized, yet widely applicable, skills found in inferential statistics, as well as additional transferable knowledge, skills, strategies, and tools to help you manage statistical work, projects, and programs more effectively.

Descriptive statistics describe data (for example, a chart or graph), whereas inferential statistics allows you one to make predictions ("inferences") based on that data. Inferential statistics are used to generate generalizations about a population using data from samples. Thus, it is clear that it gives accurate information from that definition of inferential statistics since it generates actual samples. While one is given a project to research on an issue that might be affecting the society by use of the knowledge and skills gained from the inferential class or studies can generate some data from the data obtained from the samples of the research and then help in coming up with the viable decision on how to solve such given problem. For example, in every country, statisticians are very useful when it comes to budget issues since they are brought into the board to research how the project revenues and expenses future might be, and they use inferential statistics to generate data which later they give the finance department to come up with develop the final budget. Inferential statistics is applied in budgeting, and every situation or instance that society or state faces and needs to be assessed how its impact might be in the future.

Currently working as a software engineer, the knowledge and skills, and theories gained from the statistics course, especially on inferential statistics, can help my organization predict the impacts of future changes. For example, I have the writer has been having a meeting with the strategic management team severally, and all that they foresee,. I have The writer has been able to develop software capable of working under such an environment (Specify which type of environment you are referring to here). For example, at the time of the Covid-19 pandemic, I the writer was able to helped the strategic management team make an ethical decision (What was the decision?) on workers working from home by using some software that I he developed by using the knowledge and skills gained from the statistics course, especially inferential statistics (Good!). Such a This ethical decision solved many problems (Such as?). Even now, regulations (Which regulations? Pandemic? Organizational?) have been relaxed. Some of the workers do not have to come to the workplace as they can deliver their services still at from the comfort of their homes (Anastasopoulos et al., 2020). The other advantage of this course is that it is an employment opportunity increase one’s marketability and earning potential since, at that time, companies or organizations that did not have information technology and statistics department had to incorporate it; thus, most of the individuals who had taken such course got jobs were hired.

References

Anastasopoulos, C., Weikert, T., Yang, S., Abdulkadir, A., Schmülling, L., Bühler, C., ... & Sommer, G. (2020). Development and clinical implementation of tailored image analysis tools for COVID-19 in the midst of the pandemic: The synergetic effect of an open, clinically embedded software development platform and machine learning. European journal of radiology, 131, 109233.

Trafimow, D., & MacDonald, J. A. (2017). Performing inferential statistics prior to data collection. Educational and Psychological Measurement, 77(2), 204-219.

Vijender,

Your paper is focused and has strong potential. There are, however, items to understand and address to strengthen your future work and writing. Be sure you understand the highlighted items in your paper and the summative items listed below. Using the feedback on this paper, you may revise and resubmit this paper for additional points. On your revision, be sure to remove the highlighted feedback colors (Green, red, and yellow) and make any necessary deletions/additions. Highlight revisions you make in light blue. Doing so will save time on review and grading.

· For APA style writing, use third-person voice (even when you are referring to yourself). Avoid using first- or second- person (“I”, “We”, “You”, “My” etc…)

· Ensure your ideas are clear by using specific language, explanation, and examples.

· Support your assertions with explanation/evidence.

· Avoid using unclear antecedents such as “this” or “it” unless it is clear and specific what they are referencing.

These items can quickly be addressed with commitment, study, and practice. Let me know if there is any feedback that is unclear, and I will glad to help you.

Listed below is a key to the highlighted feedback.

Highlighted Feedback Key

Red = Items recommended to delete 

Yellow = Recommended revisions 

Green = Guidance/Feedback   

Hang in there!