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Upon completion of the week 6 lesson, you will be able to:

• • Explain the concept of Classification algorithm
  • Discuss Applications of Classification algorithms
  • Explain Regression analysis
  • Validating and Testing of the Classification/Regression Models

This week reading assignment is the course textbook chapter 6 and 7 (EMC Education Service (Eds). (2015) Data Science and Big Data Analytics: Discovering, Analyzing, Visualizing, and Presenting Data, Indianapolis, IN: John Wiley & Sons, Inc).

In our classification system, we have data that is used to train our model. In this case of sorting emails into clusters, discrete values are provided with the data, and this is known as classification.

There is another aspect of supervised learning, where instead of providing a discrete value, we provide it with a continuous value. This is known as regression. Regression is also considered supervised learning. The difference between classification and regression is that the first has discrete values and the latter has continuous, numeric values.

Part I: Identifying Illegal and Unethical Application Questions (20 points)

Using the applications provided by the instructor (posted below this assignment and with chapter 6 material) find 20 illegal or unethical questions. Each answer is worth 1 point for a total of 20 points. You need to provide APA in-text citations to indicate where your information came from. Write these up on a word document following the format provided below. Failure to follow said format will result in a point deduction for the question or zero credit. You should have a “Reference” page in APA format to indicate where your answers came from. Please number your answers. Each question should contain one or two citations and rationales should be three sentences long.

Part II: Writing Interview Questions (10 points)

In this section you will write the interview questions you will ask during potential candidate interviews. These questions should assess an individual’s fit with an organization and for the position (based on the job statement, job duties/essential functions, and job specifications). These questions should also allow you to juxtapose candidates to ascertain who the most qualified candidate is.

Keep in mind the legal parameters related to interview questions, essential job functions, and the competencies you are trying to assess. What questions will assess the capabilities of the person you are interviewing, as well as the motivation to perform at a high level if given the position. Do not ask any questions that could land you in court!! Create at least 10 questions to assess the Knowledge, Skills, Abilities, and Personality of the job candidates. There should be at least two situational interview questions and two behavioral description interview questions. You may not copy these off the internet. You must create them yourself.

To accurately write interview questions you need to look at a few job descriptions as well as O*Net to understand the position you may have to hire for. By actually having a job description including; job title, job identification/job statement, job duties/job essential functions, and job specifications you will ask better questions. (You definitely should use O*Net as one of your sources for the information.)

Tell me the position and organization you are writing the interview questions for. Then write 10 interview questions. Number your interview question one 1 through 10.

Example:

Position: Women’s Soccer Coach

Organization: University of North Carolina at Pembroke

1) Situational Interview Question – Two of your star players are constantly arguing on the field during the game. What would be your short-term and long-term solutions for addressing this issue?

Important assignment parameters and reminders…

Avoid conjecture!! Provide support for your answers and indicate where you gathered supporting evidence for your suppositions in Part I. Your similarity match must be below 30% on the plagiarism detection software which means you may not just cut and paste answer for your entire paper. Some direct quotes are acceptable, but use in-text citations to reference facts you learned in an article but wrote in your own words. Papers must be posted to canvas before assignment will be graded. No late assignments are accepted without documentation of FMLA.

You must follow the “writing guidelines” posted on Canvas.

All answers should include in-text citations consistent with APA formatting style guidelines. If your paper contains plagiarized material you will receive a zero. Additionally, one point will be deducted for each APA formatting error so please review guidelines carefully.

You may use your textbook to answer questions. In addition, use the library database system to find peer-reviewed journal articles to find support for your suppositions. See directions in folder under Written Applied Assignments Module.

No websites may be used except EEOC, SHRM, and O*Net.

Answers must be in complete sentences. One point will be deducted for each incomplete sentence.

Paper Format and Directions

If the question is always illegal you need to reference 1) which application the question came from, 2) indicate the question is illegal, and 3) write out the illegal question exactly as written in application as well as 4) rationale for why the question is illegal (what law/legislation is this question breaking).

Application: Illegal, Unethical, or Potentially Illegal – “Question from application written exactly as written on application.”

Rationale – You need to provide a rationale as to why this application question is illegal, unethical, or potentially illegal. Each answer should be at least three sentences long and provide at least one or two in-text citations in proper APA format.

Example:

1) Duck Man Donuts (list application first): Illegal question – “Are you a diabetic or has anyone in your family ever been diagnosed with sugar mania?”

Rationale – According to the EEOC (2019) organizations should not ask questions about an applicant’s….. continue with rationale(s). (Answer must be two or three sentences long.)

If the question is unethical or potentially illegal you need to 1) identify application, 2) indicate the question is potentially illegal or unethical, 3) write out question exactly as written in application, and 4) “why” in this instance the question should not be asked, as well as 5) what question could be asked if any.

Example:

2) Arby’s: Potentially Illegal and Unethical Question – “Do you have reliable transportation to work?”

Rationale – Driving a personal vehicle or company vehicle is not an essential job function. This could create an adverse impact based on the American’s with Disability Act (citation) as someone may not be able to drive but could still work as a cook or cashier. (Answer must be two or three sentences long plus a separate sentence for how the application question should be written to make it ethical and avoid breaking any laws.)

They should ask: The organization is probably trying to make sure an employee will not miss shifts and will arrive to work on time. As such, they should ask, “Are you able to arrive at work on-time?” instead.

Data mining is a complex process that aims to discover patterns in large data sets starting from a collection of existing data. In my opinion, data mining contains four main steps:

1. Collecting data: This is a complex step, I will assume we have already gotten the datasets.
2. Pre-processing: In this step, we need to try to understand your data, remove or reduce noise, do dimension reduction and select proper predictors etc.
3. Feeding data mining: In this step, we need to use your data to feed your model.
4. Post-processing: In this step, we need to interpret and evaluate your model.

Classification algorithms predict one or more discrete variables, based on the other attributes in the dataset.

Regression algorithms predict one or more continuous numeric variables, such as profit or loss, based on other attributes in the dataset.

Segmentation/Clustering algorithms divide data into groups, or clusters, of items that have similar properties.

Association algorithms find correlations between different attributes in a dataset. The most common application of this kind of algorithm is for creating association rules, which can be used in a market basket analysis.

Sequence analysis algorithms summarize frequent sequences or episodes in data, such as a series of clicks in a web site, or a series of log events preceding machine maintenance.

In this assignment, you will submit a business intelligence solution
framework for a university with one online and two physical campuses.
The solution will be used by university executives to improve overall
student retention and overhead costs.

Instructions:

1. The BI solution must:

• Provide real-time data access
• Access historical institutional data from student databases from the past 15 years
• Analytic capabilities to combine data sources (i.e., students’ data,
  course registrations, online/on-campus data, dates of course offerings,
  etc.)
• Ability to predict students likely to drop out
• Easy and secure access to data from multiple divisions within the university departments
• BI dashboards to present and view the results
• Model(s) (such as: artificial neural networks [ANN], Support Vector
  Machine [SVM}, and Linear Regression [LR} models) you recommend using
  and their rationale
• You will use SAS code for the model(s) that you will use for this BI framework solution.
  
  • FOR EXAMPLE: if you’re using ANN model, write/locate ANN SAS code to include in your submission.

1. Explain in detail how your BI framework solution will work with the
   above-mentioned characteristics to help executives improve decision
   making. The executives are the CEO and president level as well as the
   vice presidents of different departments. Each department will focus on
   its own data while top executives will focus on the overall university
   total retention and costs.

Submission Requirements:

Your framework should meet the following requirements:

• Three pages in length
• Include the screenshot diagram(s) of the BI solution framework
• Formatted according to APA guidelines as explained in the CSU-Global Guide to Writing & APA (Links to an external site.) (subheadings, one-inch margins, and double spacing)
• Supported by three credible, academic outside sources in addition to course materials
• Write clearly and logically, as you will be graded on content,
  analysis, and your adherence to the tenets of good academic writing,
  which should be succinct where possible while also exploring the topics
  appropriately. Integrate and cite scholarly sources to support your
  work, and supplement your ideas.