please write a personal statement that describes your goals and the value that you bring in an academic and/or professional context (300 words or less).

1. Explain how diversity has emerged as an important (academic, political, etc ) issue in the US in particular or in the contemporary world at large.

Choose which statistic to use and conduct your analysis:

Assess the differences between Southerners and Non-Southerners on Church Attendance per Month. Below are number of days per month attended by South and non-South residents.

Describe your experience with research. Discuss your personal and academic research experiences.

a)    How did your culture and unique situation impact those experiences?
How were your experiences with research to this point similar to or different from others’ experiences? Consider the idea of “information privilege.”

b)    How will research help you achieve your personal, academic, and professional goals? What barriers exist that make it difficult for you to enter the discourse of various groups or disciplines?

c)      How can you gain access to new discourse communities?

INTELLECTUAL PROPERTY PROBLEM:

Suppose you have an assessment for a programming course. You and your classmate have an established group chat were you discuss personal and academic issues and one day you saw that they are sharing code to each other. You verified with your friends participating in the exchange that they are completely identical. Did they perform academic dishonesty or have done acts against the Intellectual Property Code? Justify your answer. As a good friend and student, what course of action will you take? What advice can you give to your friends?

Which of the case studies that you read (Walmart, Target or 5 Big Data Industries) caught your attention and why? Before reading the articles, did you think about data being used in the manner that it is? Name one other organization that may be using data warehousing and data mining techniques and explain how it is being used. Or explain how after years of collecting data how the data in the Academic Database that was implemented in Modules 6 and 7 can be useful to the academic institution? Explain your answer in 100 to 150.

Read and review the Module 1 content before responding to this discussion. Please choose one of the questions below and provide a 3-5 sentence response. What is Academic Integrity? What do you wish you would have known about plagiarism when you began your program? How does the need to uphold academic integrity impact your approach to writing assignments in the future? What are the most common reasons students plagiarize? What strategies can be used when taking notes to avoid plagiarism? Please be original No plagrasim

Read and review the Module 1 content before responding to this discussion. Please choose one of the questions below and provide a 3-5 sentence response. What is Academic Integrity? What do you wish you would have known about plagiarism when you began your program? How does the need to uphold academic integrity impact your approach to writing assignments in the future? What are the most common reasons students plagiarize? What strategies can be used when taking notes to avoid plagiarism? Please be original No plagrasim

WalMart’s fiscal year starts the first week of February. This means that when analyzing the data, week 26 is actually week 30 (26+4 weeks for January) in 2002 or the end of July 2002. Also, week 52 is actually week 4 (52+4 weeks for January 2002 minus 52 weeks for 2002) in 2003 or the end of January 2003. As an example, the spike in sales (revenue) at week 75 occurs in week 27 (75+4 weeks for January 2002 minus 52 weeks for 2002) in 2003 or the first week in July 2003. This corresponds to sales for the July 4th holiday when people are buying barbecue related items.

1. Identify spikes (outliers) in the data where extreme sales values occur and correlate these spikes with actual calendar dates in 2002 or 2003 and with holidays or special events that may occur during these periods.

Modeling the data linearly - a. Generate a linear model for this data by choosing two points.

b. Generate a least squares linear regression model for this data.

c. How good is this regression model? Output and discuss the R² value.

d. What are the marginal sales (derivative, i.e. rate of change) for this department using the linear model with two data points and the regression model?

e. Compare the two models. Which do you feel is better?

f. Remove appropriate outliers as you deem necessary and rerun the linear regression model. What is the marginal sales and discuss improvements.

2. Modeling the data quadratically - a. Generate a quadratic model for this data. Also output and discuss the R² value.

b. What are the marginal sales for this department using this model?

c. Calculate the model generated relative max/min value. Show backup analytical work.

d. Compare actual and model generated relative max/min value.

e. Remove outliers and rerun the quadratic least squares model. What is the marginal sales and discuss improvements.

3. Comparing models - a. Based on all models run, which model do you feel best predicts future trends? Explain your rationale.

b. Based on the model selected, what type of seasonal adjustments, if any, would be required to meet customer needs?