Anlaysing and intro assignment

I’m trying to study for my Computer Science course and I need some help to understand this question.

Assignment 1

Background: As noted by Kirk (2016), working with data is one of the four stages of the visualization workflow. According to Kirk (2016), “A dataset is a collection of data values upon which a visualization is based.” In this course, we will be using datasets that have already been collected for us. Data can be collected by various collection techniques.

Reference: Kirk, Andy. Data Visualisation: A Handbook for Data Driven Design (p. 50). SAGE Publications.

Assignment: Summarize 3 data collection techniques (Interviews, Surveys, Observations, Focus Groups, etc.). Compare and contrast the 3 data collection techniques you selected. Lastly, what collection techniques do you prefer and why?

Your research paper should be at least 3 pages (800 words), double-spaced, have at least 4 APA references, and typed in an easy-to-read font in MS Word (other word processors are fine to use but save it in MS Word format). Your cover page should contain the following: Title, Student’s name, University’s name, Course name, Course number, Professor’s name, and Date.

Assignment 2

Data Mining “Anomaly Detection” Assignment

Answer the following questions. Please ensure to use the Author, YYYY APA citations with any content brought into the assignment.

  1. What are Anomalies/Outliers? And what are some variants of Anomaly/Outlier Detection Problems?
  2. What are some Challenges and Work Assumptions of Anomaly Detection?
  3. Explain the Nearest-Neighbor Based Approach and the different ways to Define Outliers.
  4. Explain the Density-based: LOF Approach.
  5. Provide the General Steps and Types of Anomaly Detection Schemes.

For assignment 2 need elobrted answers with no plagrism

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