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Active 4 years, 2 months ago-
Mariam Kharazi and
Xin Zhao are now friends 4 years, 6 months ago
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Mariam Kharazi and
Aixi Wang are now friends 4 years, 6 months ago
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Mariam Kharazi and
Thara Ahmed-Sule are now friends 4 years, 6 months ago
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Mariam Kharazi and
Pierre Beasley are now friends 4 years, 6 months ago
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Mariam Kharazi and
Deja McClary are now friends 4 years, 6 months ago
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Mariam Kharazi and
Nhi Nguyen are now friends 4 years, 6 months ago
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Mariam Kharazi and
Ashlin Bungalow Puthenveedu Cheriyan are now friends 4 years, 6 months ago
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Mariam Kharazi and
Drashti Patel are now friends 4 years, 6 months ago
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Mariam Kharazi and
Sami Barhoum are now friends 4 years, 6 months ago
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Mariam Kharazi posted an update 4 years, 6 months ago
@franchesca-sterin Looking forward to potentially being classmates in future MIS courses!
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Sezgin Ayabakan wrote a new post on the site MIS Distinguished Speaker Series 4 years, 6 months ago
Humanistic Orchestration of Artificial Intelligence Applications in Real-Time Business Platform Contexts: A Rhythmic Fabric Theory
byOmar El-Sawy
Kenneth King Stonier Professor of Business […] -
Sezgin Ayabakan wrote a new post on the site Data Science Spring 2020 – Section 5 4 years, 6 months ago
Here is the exam study guide: Exam 1 Study Guide.docx
Exam Date: Feb 20, 2020 (Thursday)
Exam Time: Class Time
Exam Location: Alter 607ITAs’ Review Sessions:
Oviya: Wednesday Feb 19 from 1pm – 2pm in […]
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Information is…..
A) Data that is processed to be useful
B) Raw data
C) the study of the generalizable extraction of knowledge from data
D)Theory generalized, not yet falsifiedAnswer (A)
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What is is an inherent part of data and information?
a. Trust
b. Bias
c. Web Personalization
d. Filter BubbleAnswer: B
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Metadata is…
A) Data that describes data
B) raw, unorganized facts,
C) Big data
D) FalsifiableCorrect Answer: A
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Sezgin Ayabakan wrote a new post on the site Data Science Spring 2020 – Section 1 4 years, 6 months ago
Here is the exam study guide: Exam 1 Study Guide.docx
Exam Date: Feb 20, 2020 (Thursday)
Exam Time: Class Time
Exam Location: Alter 607ITAs’ Review Sessions:
Oviya: Wednesday Feb 19 from 1pm – 2pm in […]
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Sezgin Ayabakan wrote a new post on the site Data Science Spring 2020 – Section 5 4 years, 6 months ago
Step-by-step guideline: ICE 5.2 Telling a Story Through Visualization.docx
Finished Tableau workbook: In-Class Exercise 5.2 – Food Atlas Finished.twb
Data for Tableau workbook: In-Class Exercise 5.2 – F […] -
Sezgin Ayabakan wrote a new post on the site Data Science Spring 2020 – Section 1 4 years, 6 months ago
Step-by-step guideline: ICE 5.2 Telling a Story Through Visualization.docx
Finished Tableau workbook: In-Class Exercise 5.2 – Food Atlas Finished.twb
Data for Tableau workbook: In-Class Exercise 5.2 – F […] -
Guillermo Cordova's profile was updated 4 years, 6 months ago
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Sezgin Ayabakan wrote a new post on the site Data Science Spring 2020 – Section 1 4 years, 6 months ago
Here is the guideline: ICE 5.1 Telling a Story through Visualization
Here is the dataset: studentloans2013.xlsx
Here is the Tableau workbook: Student Loan by State – 2013.twb
Post your group’s response b […]-
2. The graphic that gives the most effective insight on the data is number of schools by type (pie) because the graphic is very clear and easy to read. The graphic is also labeled and and has good colors.
3. A graphic that is ineffective is total aid (disbursement) by school /type (bubble) because there are no labels and the graphic is hard to read because there are so many bubbles and different schools. I would recomend a different graphic for the data being used or adding labels.
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Our group Shane Clarke, Thomas Smith, Justin Cautilli
We think number 9 is the best, because it displays the data per state, and allows for the amount of aid, and what type, per state.
We think that number 6 is the worst, as it is really hard to tell what the data is about, some recommendations would be to use another type of graph.
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Group members: Zayna Mcneil, Chitra Nanavaty, Jocelynn Mitchell
1. Total Aid (Disbursement) by loan type
Why? It is simple, organized by school type, colored by load type, visually appealing, and shows the amount of loan.
2. Total Aid (Disbursement) by School
Why? The graph has no labels, no legend, no title, is hard to see, and data unclear. We reccommend adding a title, a legend, and labels. -
Gia Thai Pham, Ryan Brandstetter – 005
The best: Total Aid (Disbursement) by School/Type (Treemap) – explantion: it shows the aid that each school gives and type of the school.
The worst: Number of Schools by Type (Bar) – explanation: we can’t know how specific it is for each school. We just know the number of school -
Ethan & Alyssa Piselli & Ian Hauser
2. Total Aid by School Type by State
—-Effective because it’s very organized and easy to read and understand. Breaks each individual territory up so you can get a gauge on how different areas of the country distribute aid3. Total Aid (Disbursement) By School
—-Setup has nothing to do with the data. Splits it between type of data and the total aid of each school but you have to go through every single dot to assess it. Doesn’t give aggregate data, no overall viewpoint.
—-Changes? Spread the data out more; some of the bigger circles mask the smaller ones (very difficult to pull data up from each circle present. Color changes to shade each area based on dollar amount of aid. -
Kevin Publicover, Christine Boligitz, Ivy Zhong, Allen Huang.
2. We liked the Data aid disbursement by loan type, bar chart. Easy to comprehend and compare based on loan type. The other charts are not as straightforeward in comparison.
3. Total aid disbursement by school, packed bubbles. We dont think this is the most effective type of graph to use because hard to compare. It would be easier to comprehend if we added labels.
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Aung Zaw
Ishika Kedia Chaw Su
Jeongmin Shin1)The most effective at giving insight into the data is Aid (Disbursement) by Loan type as it is clear and detailed and also has an informative overview.
2) The Least effective graph is Total Aid (Disbursement) by School/Type (Bubble) because it looks complicated and there are no texts or labels on the graph to give a general overview of the graph.
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Sezgin Ayabakan wrote a new post on the site Data Science Spring 2020 – Section 5 4 years, 6 months ago
Here is the guideline: ICE 5.1 Telling a Story through Visualization
Here is the dataset: studentloans2013.xlsx
Here is the Tableau workbook: Student Loan by State – 2013.twb
Post your group’s response b […]-
Connor McShane, Sean Gallagher, Tyler Edwards, Owen Murphy – 005
1. The graph that we think most effectively portrays the data is the treemap. The ability to distinguish between the rankings using the color of the square as well as the size of the square provides the reader with an easy to understand diagram.
2. The graph that we believe least effectively portrays the data is the packed bubbles visualization. This visualization is hard to read without hovering over each label to distinguish the different characteristics. It also is not that appealing visually, as it is hard to look at and a little bit harder to understand than it needs to be.
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Shivam Patel- 005
1. I think the bar graph with total aid (disbursement) by Loan is structured well by showing the different values for each school type and splitting them into 3 different categories.
2. I think the least effective one is the pie graph as its only a generalized and has the least of amount of information. -
Total Aid by School Type By State – In our opinion this is the most effective because the visual is easy to understand and the charts are broken up by state and within the state there is more data for the viewer to see.
Total Aid by School Type by State- this one is the the least effective because there is just raw data and the viewer has no visuals to make seeing the data easy
-Shivani Naik, Maya Krishnamurthy, Amanda Mewbourn. Daniel Roh
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Sezgin Ayabakan wrote a new post on the site Data Science Spring 2020 – Section 5 4 years, 6 months ago
Here is the guideline: ICE 4.2 – Gotta Catch Em All.docx
Here is the data: pokemon.xlsx
This is a GRADED ICE! -
Sezgin Ayabakan wrote a new post on the site Data Science Spring 2020 – Section 1 4 years, 6 months ago
Here is the guideline: ICE 4.2 – Gotta Catch Em All.docx
Here is the data: pokemon.xlsx
This is a GRADED ICE! - Load More