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Laurel Miller wrote a new post, Weekly Question #5: Complete by February 28, on the site Data Science: Honors 3 days, 16 hours ago
Leave your response as a comment on this post by the beginning of class on February 28. Remember, it only needs to be three or four sentences. For these weekly questions, I’m mainly interested in your o […]
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Laurel Miller wrote a new post, Study Guide for Exam 1, on the site Data Science: Honors 4 days, 2 hours ago
Here is the study guide for the first midterm exam.
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Laurel Miller wrote a new post, Study Guide for Exam 1, on the site Data Science 4 days, 2 hours ago
Here is the study guide for the first midterm exam.
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Laurel Miller wrote a new post, In-Class Exercise 5.2: Creating Infographics, on the site Data Science 4 days, 4 hours ago
Here is the exercise.
And here is the graphic file you’ll need: Philadelphia Area Obesity Rates.png.
Right-click on the file and save it to your computer.
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Laurel Miller wrote a new post, In-Class Exercise 5.2: Creating Infographics, on the site Data Science: Honors 4 days, 4 hours ago
Here is the exercise.
And here is the graphic file you’ll need: Philadelphia Area Obesity Rates.png.
Right-click on the file and save it to your computer.
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Laurel Miller wrote a new post, Reading Quiz #5: Complete by February 26, on the site Data Science: Honors 5 days, 18 hours ago
Some quick instructions:
You must complete the quiz by the start of class on February 26.
When you click on the link, you may see a Google sign in screen. Use your AccessNet ID and password to sign in. […] -
Laurel Miller wrote a new post, Reading Quiz #5: Complete by February 26, on the site Data Science 5 days, 18 hours ago
Some quick instructions:
You must complete the quiz by the start of class on February 26.
When you click on the link, you may see a Google sign in screen. Use your AccessNet ID and password to sign in. […] -
Laurel Miller wrote a new post, In-Class Exercise 5.1: Telling a Story Through Visualization, on the site Data Science 6 days, 4 hours ago
Here is the exercise.
Before you start, save this Tableau file and the studentloans2013 Excel workbook to your computer. Remember, to save the file right-click on the link and choose “Save As…” (don’ […]
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Laurel Miller wrote a new post, In-Class Exercise 5.1: Telling a Story Through Visualization, on the site Data Science: Honors 6 days, 4 hours ago
Here is the exercise.
Before you start, save this Tableau file and the studentloans2013 Excel workbook to your computer. Remember, to save the file right-click on the link and choose “Save As…” (don’ […]
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Laurel Miller wrote a new post, Office hours for February 12, on the site Data Science: Honors 6 days, 12 hours ago
My office hours for February 12 have been changed to 11:00am-12:00pm
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Laurel Miller wrote a new post, Office hours for February 12, on the site Data Science 6 days, 12 hours ago
My office hours for February 12 have been changed to 11:00am-12:00pm
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Laurel Miller wrote a new post, Discussion Question #3: What is the most important…………?, on the site Industry Experience in MIS 1 week ago
What are the most important skills (business/technical) and people that you have discovered in your internship? Is there a skill that you didn’t have before but realize that you absolutely need? Is there a per […]
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After working for a month, I realized organizational skill is very important. As work keeps going, there’re plenty of meetings and new information everyday that I need to note down. Organizing my OneNote with different sections and pages such as meetings, to-do, personal learnings, things I can share with the team and things I keep for myself, etc. is essential. At the same time, other interns are very important (peer). There was another intern in my team who joined the team a quarter before me so he knows about the team better than I do. I also feel comfortable to run to him for “silly” questions that I don’t want to bother my boss. He also provides me with his own insights and tips about team culture and work. Who doesn’t need a peer who can both teach us and joke around with us?
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I started my internship before I took MIS3535 and to a PM, MS Project is very important. It was very similar to Excel and not too difficult to pick up on my own. Communication was not my strong suit either; however, I also had to improve communication skills to do my job well. My co-worker, who sits next to me, is the only other girl on my team and I find that being friends with her helps me feel more comfortable at work.
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So far from working here I have discovered that Tableau and Excel skills are very important. I constantly assist with updating and creating dashboards using Tableau. The complexity of the dashboards and the enormous Excel spreadsheets that are sent to me can be very overwhelming. Luckily at Fox I have taken courses that have given me a great introduction on how to to use these programs but there are still so many more tools inside these programs I have yet to learn and play around with. For example, on my second week I used the splicing tool in Excel for the first time and just the other day I learned how to use Tableau Prep. If I’m ever unsure on how to use anything I usually ask my team and they do a great job at explaining how to do things. I discovered that I want everyone on my team in Global Operations to be on my side because they are all very knowledgeable.
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Laurel Miller wrote a new post, Weekly Question #4: Complete by February 14, on the site Data Science: Honors 1 week, 3 days ago
Leave your response as a comment on this post by the beginning of class on February 14. Remember, it only needs to be three or four sentences. For these weekly questions, I’m mainly interested in your op […]
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I believe the most important core principle of data visualizations is asking “why.” Most people have the capacity to dissect what is occuring in a good visualization, however not many people take the time or effort to understand why such results are happening. Part of the reason visualizations are created is to attract people into asking “why”–but if people aren’t doing that, then they are simply mindlessly consuming useless data, and the purpose for the data and visualizations become lost.
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I think the most important principle is simplify without oversimplifying. Often times when I read a data-driven article, my eyes look for a data visualization that can help me quickly understand what the article is trying to communicate. When a data visualization can capture the “essence” of data, it really helps boil down and even strengthen the argument that the article is making. Plus, it saves time! That’s why I think tools like Tableau are extremely powerful in the business world. When we’re inundated with too much information, a data visualization that can quickly communicate the idea within 5 seconds is superb.
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I think the most important principle for data visualizations is to ask “why.” Data visualizations are made to help us interpret data by looking at them in different and usually more visually appealing formats. Once you have both analyzed and formatted the data the next step is to attempt to find the cause behind them. There is almost always an explanation for why the data are the way they are so I think it’s important that data visualizations include this next step or at least provide some insight into the reasoning behind it. With access to all these data, and with more and more resources and tools being created to display data, what should naturally come next is some sort of deduction towards the root of the pattern the data display.
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I believe that the most important principle on data visualization would be to explore. The reason for this is that without really looking at the data, we may miss an important factoid or reasoning for the data points to come in like this. If we don’t explore the data and discover things, our conclusions may only scratch the surface and may become limited to what we already know or assumed.
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I think the most important data visualization is “explore”. I believe that a great infographic will give the viewer the necessary data and background info for them to draw their own insights as well as encourage their intellectual curiosity about a subject. You will never be able to fit every piece of relevant data on one infographic. It should give you the main points and build a foundation for you to explore solutions and ideas.
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I believe “be skeptical” is important because accepting data without wondering what went into it is very dangerous. The best way to understand something is to question where it came from and why it is the way that it is. In order to do that, skeptically looking at the answers you are given and trying to understand how they came to be make certain that you know your data is providing good answers. By questioning the data, we can get the most out of the data.
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I believe that the most important principle is the explore principle. When someone constructs a data visualization, they construct in a way that explores the data allowing the viewer to discover things. The art of exploring a data visualization will heighten its capabilities of visualizing data and will allow the viewer to gain more from it.
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I agree with a number of my colleagues above: “be skeptical” is perhaps the most important to me of the eight listed.. In addition to the reasons given and already expounded upon (verifying collection methods, considering the influence of an agenda, etc.), I think it’s critical to be skeptical of the data because failing to do so, unlike some of the other core principles, does not simply make the data potentially less useful. A failure to be skeptical might make us better off without having the result in the first place. Misleading or inaccurate data can be dangerous, and a skeptical attitude is one reasonable safeguard against that.
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Laurel Miller wrote a new post, In-Class Exercise 4.2: Getting Familiar with Tableau, on the site Data Science 1 week, 4 days ago
Here is the exercise.
And here is the spreadsheet you’ll need to complete the exercise [In-Class Exercise 4.2 – FoodAtlas.xlsx].
Make sure you right-click on the Excel file link and select “Sa […]
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Laurel Miller wrote a new post, In-Class Exercise 4.2: Getting Familiar with Tableau, on the site Data Science: Honors 1 week, 4 days ago
Here is the exercise.
And here is the spreadsheet you’ll need to complete the exercise [In-Class Exercise 4.2 – FoodAtlas.xlsx].
Make sure you right-click on the Excel file link and select “Sa […]
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Laurel Miller wrote a new post, Reading Quiz #4: Complete by February 12, on the site Data Science 1 week, 5 days ago
Some quick instructions:
You must complete the quiz by the start of class on February 12.
When you click on the link, you may see a Google sign in screen. Use your AccessNet ID and password to sign in. […] -
Laurel Miller wrote a new post, Reading Quiz #4: Complete by February 12, on the site Data Science: Honors 1 week, 5 days ago
Some quick instructions:
You must complete the quiz by the start of class on February 12.
When you click on the link, you may see a Google sign in screen. Use your AccessNet ID and password to sign in. […] -
Laurel Miller wrote a new post, In-Class Exercise 4.1: Finding Good and Bad Visualizations, on the site Data Science 1 week, 6 days ago
Here is the exercise
Here are the links in case you cannot click from the document.
History, Economics and Social Issues
Science and Health
English, Fine Arts and Entertainment
Remember to […]
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Laurel Miller wrote a new post, In-Class Exercise 4.1: Finding Good and Bad Visualizations, on the site Data Science: Honors 1 week, 6 days ago
Here is the exercise
Here are the links in case you cannot click from the document.
History, Economics and Social Issues
Science and Health
English, Fine Arts and Entertainment
Remember to […]
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Laurel Miller wrote a new post, Assignment 1: Analyze a Data Set Using Tableau, on the site Data Science 1 week, 6 days ago
Here is the assignment.
Here is the worksheet as a Word document to make it easy to fill in and submit (along with your Tableau file).
And here is the data file you will need to complete the assignment […]
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https://projects.fivethirtyeight.com/trump-approval-ratings/?ex_cid=rrpromo
This article uses results from national polls to estimate the approval rating of President Donald Trump. The data, which is adjusted according to each poll’s quality, recency, sample size, and partisan lean, concludes that as of midnight 2/16/2019, approximately 54% of Americans disapproved of President Trump, while 41.7% approved, and less than 5% failed to have an opinion. The data is also used to compare the approval rating of Trump to the twelve previous presidents at different points throughout their term. This data is interesting because it proves that Trump is more disliked than any of the twelve presidents before him. It is also relevant, to all of us, because these results will likely have an effect on whether Trump gets re-elected in 2020 and continues to run our country.
This article by Jared Dubin goes into detail about how awful the NBA’s Southeast division actually is. In the history of the league, a division winner has never been under .500 and it is looking like that will happen within this division this year. A very interesting thing about this is that each of the Southeast teams have a losing record even with the opportunity to get wins against the other teams in the division. Even when adjusting for schedules, they are still outscored by 3.050 points which is fifth worst in NBA history. He ends his article with the fact that maybe due to this, the NBA will change to an open seeded playoff system.