Week 7 Interactivity Research Assignment

Background:  Applying the material covered in Chapter 6 and now in Chapter 7  specifically focusing on Interactivity, the assignment for this chapter  will analyze the gallery of 49 chart types from Chapter 6 and provide  the following for 5 of your choice.

1.  Select 5 chart type options from the gallery of 49 presented in Chapter 6

2.  For  each, select 3 of the 5 most often used data adjustment features and  for each describe in detail how you would apply each to each of the 5  chart types. Example for one: Chart Type Selected – Word Cloud.  The 3  Data Adjustments selected: Contributing – force input from the  viewer/user to select one word from a drop-down list before moving  forward with the display. The results would display the visualization  with the stats for the word the viewer/user selected.  The format for  this information should be in a table format with no attempt for full  sentences.

3.  Immediately  following this table, provide your perspective related to any problems,  issues or constraints in selecting 3 data adjustment features for each  chart type selected. You do not have to use the same data adjustment  features for each chart type.  An example of issues could be after  selecting a Stream Graph and a Framing data adjustment feature, any  example I developed did not make sense.  I also had to change the data  adjustment feature of navigating as my first choice because I could not  think of an example to fit the data and chart type.   Do NOT use any  suggestion if any is provided in the text for interactivity.  Do not  copy my examples. You must not copy and paste any information from the  text from the pages in the gallery.  You must apply what you have  learned from the previous chapters and not copy and paste from other  sources.  When you do use other sources to help gather any knowledge  such as the text and other online materials such as the book companion  site or the library, include each as a source on the reference page  following APA formatting.

4.  For  each chart type selected, provide examples for each of the 3  Presentation adjustments and why those examples fit the data and chart  type.  Again, use a table format instead of attempting sentences.

5.  Immediately  following this table, provide your perspective related to any problems,  issues or constraints in developing the examples of the 3 Presentation  adjustments for each chart type selected. An example could be after  selecting a Waffle Chart and a Focusing presentation adjustment feature,  I had to develop 4 examples before the final choice made sense.  Do NOT  use any suggestion if any is provided in the text for interactivity. Do  not copy any example I provided.  You must not copy and paste any  information from the text from the pages in the gallery.  You must apply  what you have learned from the previous chapters and not copy and paste  from other sources.  When you do use other sources to help gather any  knowledge such as the text and other online materials such as the book  companion site or the library, include each as a source on the reference  page following APA formatting.

6.  In  a conclusion, provide your reflection on the chapter contents, the  material and discussions in the discussion forum, and the efforts to  complete the above requirements to include how these activities and  knowledge will assist you in the future for your data visualization  projects.  These future projects could be the possible initiations at  your organization or personal effort or maybe an upcoming class or  degree requirement.

Your  research paper should be at least 3 pages (800 words), double-spaced,  margins are normal, have at least 4 APA references, and typed in an  easy-to-read consistent font family (size no lager than 12) 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. 

R or weka Lab

  

Laboratory I:

         

To download additional .arff data sets go to:

http://www.hakank.org/weka/

or search the Internet for .arff files required

· What’s the difference between a “training set” and a “test set”?

· Why might a pruned decision tree that doesn’t fit the data so well be better than an un-pruned one?

· What’s the first thing that 1R does when making a rule based on a numeric attribute?

· How does 1R avoid overfitting when making a rule based on an enumerated and/or numeric attribute?

· What is the difference between Attribute, Instance and Training set? 

  • What      is the difference between ID3 and C4.5?
  1. Use the following learning      schemes to analyze the iris data (in iris.arff): 

  

OneR

– weka.classifiers.OneR

 

Decision table

– weka.classifiers.DecisionTable -R

 

C4.5

– weka.classifiers.j48.J48

· Do the decisions made by the classifiers make sense to you? Why?

· What can you say about the accuracy of these classifiers? When classifying iris that has not been used for training? 

· How did each one of the methods perform?

  1. Use the following learning      schemes to analyze the bolts data (bolts.arff without the TIME attribute):      

  

Decision Tree

– weka.classifiers.j48.J48

 

Decision table

– weka.classifiers.DecisionTable -R

 

Linear regression

– weka.classifiers.LinearRegression

 

M5′ 

– weka.classifiers.M5′

· The dataset describes the time needed by a machine to produce and count 20 bolts. (More details can be found in the file containing the dataset.) 

· Analyze the data. What adjustments have the greatest effect on the time to count 20 bolts? 

· According to each classifier, how would you adjust the machine to get the shortest time to count 20 bolts?

  1. Produce      a model for both Weather and Weather.nominal data sets. Which method(s) did you use? What did      the tree(s) look like?

Laboratory II:

 

To download additional .arff data sets go to:

weka data folder for

BreastTumor.arff

http://www.hakank.org/weka/

zoo.arff, wine.arff, bodyfat.arff, sleep.arff, pollution.arff

  1. Use the following learning schemes to analyze the zoo      data (in zoo.arff): 

  

OneR

– weka.classifiers.OneR

 

Decision table

– weka.classifiers.DecisionTable -R

 

C4.5

– weka.classifiers.j48.J48

 

K-means

– weka.clusterers.SimpleKMeans

Try using reduced error pruning for the C4.5. Did it change the produced model? Why? 

For K-means, for the first run, set k=10. Adjust as needed. What was the final number of k? Why?

  1. Use the following learning schemes to analyze the      breast tumor data. 

  

Linear regression

– weka.classifiers.LinearRegression

 

M5′ 

– weka.classifiers.M5′

 

Regression Tree

– weka.classifiers.M5′

 

K-means clustering

– weka.clusterers.SimpleKMeans

A) How many leaves did the Model tree produce? Regression Tree? What happens if you change the pruning factor? 

How many clusters did you choose for the K-means method? Was that a good choice? Did you try a different value for k?

B) Now perform the same analysis on the bodyfat.arff data set.

  1. Use a      k-means clustering technique to analyze the iris data set. What did you      set the k value to be? Try several different values. What was the random seed value?      Experiment with different random seed values. How did changing of these values      influence the produced models?
  2. Produce      a hierarchical clustering (COBWEB) model for iris data. How many clusters did it produce? Why?      Does it make sense? What did you expect?

Change the acuity and cutoff parameters in order to produce a model similar to the one obtained in the book. Use the classes to cluster evaluation – what does that tell you?

Laboratory III:

 

To download additional .arff data sets go to:

http://www.hakank.org/weka/

zoo.arff, wine.arff, soybean.arff, zoo2_x.arff, 

sunburn.arff, disease.arff

8. Use the following learning schemes to compare the training set and 10-fold stratified cross-validation scores of the disease data (in disease.arff): 

  

Decision table

– weka.classifiers.DecisionTable -R

 

C4.5

– weka.classifiers.j48.J48

 

Id3

– weka.clusterers.Id3

A) What does the training set evaluation score tell you? 

B) What does the cross-validation score evaluate? 

C) Which one of these models would you say is the best? Why?

9. Use the following learning schemes to analyze the wine data (in wine.arff). 

  

C4.5

– weka.classifiers.j48.J48

 

Decision List

– weka. classifiers.PART

A) What is the most important descriptor (attribute) in wine.arff?

B) How well were these two schemas able to learn the patterns in the dataset? How would you quantify your answer?

C) Compare the training set and 10-fold cross-validations scores of the two schemas.

D) Would you trust these two models? Did they really learn what is important for proper classification of wine?

E) Which one would you trust more, even if just very slightly?

10. Perform the same analysis of sunburn.arff as in 2. Instead of 10-fold cross-validations use 5-fold.

A)-E) Same as in 2.

F) Why could not we use 10-fold evaluation in this example?

11. Choose one of the following three files: soybean.arff, zoo.arff or zoo2_x.arff and use any two schemas of your choice to build and compare the models.

Disucssion

 

  • Describe the difference between statistical significance and practical significance.
  • What assumptions are necessary to perform a large sample test for the difference between two populations means?

security architecture 9.1

 If an attacker can retrieve the API and libraries, then use these to write an agent, and then get the attacker’s agent installed, how should Digital Diskus protect itself from such an attack? Should the business analytics system provide a method of authentication of valid agents in order to protect against a malicious one? Is the agent a worthy attack surface? 

Movement of traditional IT Staff

 

The main focus is on the movement of traditional IT staff.  To facilitate cultural assimilation, IT and non-IT must become more integrated.  What are some strategies to implement to allow this type of interaction to occur?

Note: The first post should be made by Wednesday 11:59 p.m., EST.

Your response should be 250-300 words. 

Enterprise Risk Management

 

Chapter 6 presented the approach the LEGO Group used to implement ERM, and chapter 9 presented a discussion and case study on implementing ERM in a higher education environment. Please explain how ERM adoption and implementation in the higher education (HE) environment differs from the for-profit environment. Cite specific examples from this week’s readings.

To complete this assignment, you must do the following:

A) Create a new thread. As indicated above, explain how ERM adoption and implementation in the higher education (HE) environment differs from the for-profit environment. Cite specific examples from this week’s readings. In your explanation, discuss at least three points or aspects in which the implementing ERM in the two environments differ.

500 Words

IT-project management DQ5A

 

You will be asked to fill various needs within an organization. Troubleshooting is not like throwing darts. It is a methodical process based on what you know about computer issues and behaviors. Please answer all of the following issues.

  1. My computer made a screaming noise like a girl on a rollercoaster. Now it will not turn on. What happed to the computer? Was that its death scream? Do all computers do this after a year of use? What are possible causes? How will you address the issue?
  2. I was about to shut down this computer yesterday, an error popped out “There is another user logging onto this computer. If you shut it down will cause them to lose data.” I’m afraid to shutdown my computer because someone else is using it. Who is on my computer? How do you handle this request?
  3. One of your clients brings their laptop to you and says it seems really hot on the bottom. Explain some of the possible causes. How do you handle this request?

InfoTech Import in Strat Plan (ITS-831)

Research Paper: Develop a Computer/Internet Security Policy

Word count: 2 to 3 pages

You have been hired as the CSO (Chief Security Officer) for an organization. Your job is to develop a very brief computer and internet security policy for the organization that covers the following areas:

Computer and email acceptable use policy

Internet acceptable use policy

Make sure you are sufficiently specific in addressing each area. There are plenty of security policy and guideline templates available online for you to use as a reference or for guidance. Your plan should reflect the business model and corporate culture of a specific organization that you select. 

Include at least 3 scholarly references in addition to the course textbook. At least two of the references cited need to be peer-reviewed scholarly journal articles from the library.

Your paper should meet the following requirements:

Be approximately 2-4 pages in length, not including the required cover page and reference page.

Follow APA7 guidelines. Your paper should include an introduction, a body with fully developed content, and a conclusion.

Support your answers with the readings from the course and at least three scholarly journal articles to support your positions, claims, and observations, in addition to your textbook. The UC Library is a great place to find resources.

Be clearly and well-written, concise, and logical, using excellent grammar and style techniques. You are being graded in part on the quality of your writing.

Reading resources:

1. Chapter 10, “Information Systems Sourcing”

Text book: Managing and Using Information Systems, Keri E. Pearlson, Carol S. Saunders, Dennis F. Galletta, John Wiley & Sons

2. Chapter 10, “Information Systems Sourcing” pp. 224-234

Buhrendorf, E. (2019). Outsourcing IT is a money-saving cyber safety net for company data. Fairfield County Business Journal, 55(20), 12. Retrieved from http://search.ebscohost.com/login.aspx?direct=true&AuthType=shib&db=b9h&AN=136657455&site=eds-live

plagiarism check required, Good work, APA format, include References, within 8hrs

project 2

 You will type a three to five-page paper on the various types of Social Media Analytics. You may use the textbook in addition to researching the internet for additional sources. Please submit your APA-formatted paper in a Word document. Your paper must be double spaced and include a cover page and a reference page for your cited sources. Please note that the reference page and cover page do not count towards your paper’s three to five pages in length. Please note that this project is 25 % of your grade.