-
Laurel Miller wrote a new post on the site MIS 0855: Data Science Spring 2017 8 years ago
Here is the study guide for the third (final) exam.
-
Laurel Miller wrote a new post on the site MIS 0855: Data Science Spring 2017 8 years ago
Here is the link for the driver download
-
Laurel Miller wrote a new post on the site MIS 0855: Data Science Spring 2017 8 years ago
Here is the link for the driver download
-
Laurel Miller wrote a new post on the site MIS 0855: Data Science Spring 2017 8 years ago
Here is the exercise.
And here is the spreadsheet you’ll need [In-Class Exercise 13.2 – VandelayOrdersAll.xlsx].
-
Laurel Miller wrote a new post on the site MIS 0855: Data Science Spring 2017 8 years ago
Here is the exercise.
And here is the spreadsheet you’ll need [In-Class Exercise 13.2 – VandelayOrdersAll.xlsx].
-
Laurel Miller wrote a new post on the site MIS 0855: Data Science Spring 2017 8 years ago
Here is the exercise
-
Laurel Miller wrote a new post on the site MIS 0855: Data Science Spring 2017 8 years ago
Here is the exercise
-
Laurel Miller wrote a new post on the site Industry Experience in MIS-SPRING 2017 8 years, 1 month ago
Please be sure to check the gradebook for any unanswered discussion questions or missing status reports. The final powerpoint is due May 1. Your eportfolio page should also be completed at that time. If you on […]
-
Laurel Miller wrote a new post on the site MIS 0855: Data Science Spring 2017 8 years, 1 month ago
Leave your response as a comment on this post by the beginning of class on April 20, 2017. Remember, it only needs to be three or four sentences. For these weekly questions, I’m mainly interested in your o […]
-
Laurel Miller wrote a new post on the site MIS 0855: Data Science Spring 2017 8 years, 1 month ago
Leave your response as a comment on this post by the beginning of class on April 20, 2017. Remember, it only needs to be three or four sentences. For these weekly questions, I’m mainly interested in your o […]
-
For Blackboard:
Columns would be course, the semester, grade, professor
Rows: the name of the course, SPR/FALL, A-F, name of professor -
For Snapchat,
The rows will be each person you snapchat.
The columns can hold data relating to each person you snapchat, such as friend information (name, username, snap score, etc), friend emojis, and time stamps, etc. -
For Facebook:
The rows would be your friends
The columns would be information about that person such as their latest postd, birthday, where they live, etc. -
For the bank account,
The row would be each transaction.
The columns would be the place of the transaction, the amount of money in the transaction, the available amount of money left in the account. -
For an Amazon purchase,
The rows would be the name of the person the item is for
The columns would be the transaction number, the address to send the item to, name of the item -
For Instagram,
The rows would be the individual’s profile
The columns would be the followers and the people one is following -
For Youtube,
The rows would be the Video Name
The column would be the description, how long the video is, and what kind of video it is. -
For Twitter,
The rows would be each individual’s Twitter name.
The columns could include: how many that Twitter account follows, how many follow that Twitter account, how many tweets that Twitter account has, how many media tweets (images/videos) that Twitter account has, etc. -
For facebook,
The Row would be the name of a user’s account
The columns would be how many posts they have, how many likes they get, how often they post, how many friends they have, how often they comment on other posts, etc.
-
A data-driven service I use regularly is email. The rows of data would subject line and the columns would be recipient, whether or not there were attachments, length of the message, and date sent.
-
For a blog,
The rows would be the blog entries.
The columns could be entry name, date, word count, views/impressions, and number of comments. -
For the Stock App on the iPhone,
Rows: Stocks names,
Columns: 52W high, 52W low, Current price, and whether it was positive or negative from the previous day. -
For a news app
Rows – Each individual story
Columns – Topics/Categories for type of stories -
For Uber or Lyft:
Rows would be the customer IDs
Columns would be Driver ID, Cost of Trip, Time of Pickup, Time of Dropoff, and the Rating of Trip out of 5 stars -
For Seeking Alpha (Stock Market Application)
Rows: Would include an individual security & what sector of the market it resides with. Could include possible competitors.
Columns: This can include the current price per share, dividend payment, current return, cost basis, etc. -
For WhatsApp Messenger (Messaging App):
The rows would be your contacts/friends’ number
The columns would be information about the chat history with that person, such as the time of the first and last message, number of photos and videos sent, how many group chats in common, number of voice notes sent in the conversation, etc. -
For Blackboard:
The columns would be:
-Course
-Professor
-Weekday/Time
-Prior Feedback
-Assignments
The rows would be:
-Course name
-Professor name
-Student Feedback and Ratings
-Prior semester assignments -
For Blackboard, each row data would correspond to the column heading. The column headings would be: Course ID, Course Name, Professor, Course Grade.
-
A data source I use often is ESPN for golf.
The rows would be the rankings.
The columns are their names, age, events played, rounds played, cuts made. -
A data source I use often is ESPN for statistics on players. For baseball players the rows would be the players names and the columns would be their statistics such as batting average, singles, doubles, triples, home runs, strikeouts, etc.
-
For Youtube, the rows could be who you are subscribed to and the columns could be their video uploads, their number of subscribers, the amount of views they’ve had, and their specific playlists.
-
For Facebook:
The rows would be the name of the users you are friends with, including their full name. While the columns would represent information about them such their posts, sex, date of birth, relationship status, their bio, family members and number of Facebook friends they have. -
For your calendar
The columns would be the numerical days
The rows would be the days of the week -
For Netflix
The rows would be ratings (1-5)
the columns would be all their movies on file and past movies and or tv shows they have removed -
For Amazon.com
The rows would be the particular items in stock.
The columns would be item name, item ID, item cost, source location, shipping cost, item description -
For Facebook, the columns can be what the user’s posts, how many things they share, how many posts they like and comment.
The rows would be the user accounts. -
For Draft Express (NBA Mock Draft Website)
The rows would represent each draft pick
The columns would represent the team, projected prospect, prospect physical attributes, and stats. -
For NBA players’ statistics.
The row would be players’ name.
The colimns woud be PPG, RPG, APG, BPG, SPG, FGP, TPM, TPP and FPPG. -
For Snapchat:
Rows would be people that i snap chat or people thats on my contact list
The columns would be the number of times i snap them in a week, month and year. Also some usfull information would be how long the average snap is to that specific person. -
For Google Finance:
Rows would be individual Companies
Columns would be stock price, beta, P/E ratio, and other describing data and ratios that are given -
For WeChat (similar to iMessage),
The rows would be each person’s photo and name.
The columns would be the text, emojis, links, photos or video you sent to each other. -
For Instagram:
Columns: Can be the number of posts, followers and the number of people a person follows.
Rows: Can be the number of likes and comments on particular posts, DM’s (direct messages), and follow requests from individuals. -
For Instagram,
Columns: number of posts, number of followers, number of following
Rows: Likes, comments; given and received, locations, tagged posts -
For Gmail:
Columns: Messages, time, attachments, word count
Rows: Sender, receiver -
For Facebook –
Rows: name of the friend
Columns: information related to the friend such as age, gender, date of birth, relationship status, number of friends, number of posts, number of photos/videos
-
For Blackboard,
Columns: Courses, Grades, Calendar, etc.
Row: Name of the course, specific grade A-F, due dates, etc. -
Facebook
Columns: Locations, Posts, Comments, Likes, Friends
Rows: Name, age, address -
Twitter
Row: Name of account
Column: Tweets, followers, who you follow -
A regular data driven software that I regularly use is Bloomberg.
Some of the common column names that i would associate with the financial software are: Last Price, Price to Earnings Ratio, Enterprise Value, Debt to Equity Ratio, and Free Cash Flow.
For the rows I would show the Date and its frequency, which would elaborate on the specific time period of the financial values.
-
For Facebook
Row: User
Columns: Age, Education, Job, Address, # of Friends. -
For Instagram:
Rows: username
Columns: Amount of pictures posted, average likes on pictures, amount of followers, amount of people they are following. -
For meetings that are available for me to attend my support group:
Filter – Days of the week
Row: meeting names
Columns: time – location – type – open/closed -
For Magic Cards:
Rows: Individual Cards
Columns: Mana cost, type, Rules text, artist -
For Facebook:
The rows would be friends names
The columns would be information about them (such as birthdays), new posts (such as pictures or status), their friendship with you (past pictures and posts), and other info on Facebook. -
For Blackboard, the rows could be the courses you take(most likely separated by semester). The rows could probably be things like, your grade for each course, the content, the(each) syllabus, announcements, updates, pretty much every tab that each course shares.
-
For Amazon:
The rows would be: Individual Items that I’ve bought.
Columns: Date Bought, Price, Quantity
-
-
Laurel Miller wrote a new post on the site MIS 0855: Data Science Spring 2017 8 years, 1 month ago
Here is the exercise.
And here is the spreadsheet you’ll need for the exercise [In-Class Exercise 12.2 – Sentiment Analysis Tools.xlsx].
-
Laurel Miller wrote a new post on the site MIS 0855: Data Science Spring 2017 8 years, 1 month ago
Here is the exercise.
And here is the spreadsheet you’ll need for the exercise [In-Class Exercise 12.2 – Sentiment Analysis Tools.xlsx].
-
Laurel Miller wrote a new post on the site MIS 0855: Data Science Spring 2017 8 years, 1 month ago
Some quick instructions:
You must complete the quiz by the start of class on April 18, 2017.
When you click on the link, you may see a Google sign in screen. Use your AccessNet ID and password to […] -
Laurel Miller wrote a new post on the site MIS 0855: Data Science Spring 2017 8 years, 1 month ago
Some quick instructions:
You must complete the quiz by the start of class on April 18, 2017.
When you click on the link, you may see a Google sign in screen. Use your AccessNet ID and password to […] -
Laurel Miller wrote a new post on the site MIS 0855: Data Science Spring 2017 8 years, 1 month ago
Class will start at 1:00pm on April 13
-
Laurel Miller wrote a new post on the site MIS 0855: Data Science Spring 2017 8 years, 1 month ago
Here is the exercise.
-
Laurel Miller wrote a new post on the site MIS 0855: Data Science Spring 2017 8 years, 1 month ago
Here is the exercise.
-
Laurel Miller wrote a new post on the site MIS 0855: Data Science Spring 2017 8 years, 1 month ago
Here is the exercise.
Here is the excel spreadsheet you will need to complete this exercise [In-Class Exercise 11.2 – NCAA 2013-2014 Player Stats]
-
Laurel Miller wrote a new post on the site MIS 0855: Data Science Spring 2017 8 years, 1 month ago
Here is the exercise.
Here is the excel spreadsheet you will need to complete this exercise [In-Class Exercise 11.2 – NCAA 2013-2014 Player Stats]
-
Laurel Miller wrote a new post on the site MIS 0855: Data Science Spring 2017 8 years, 1 month ago
Leave your response as a comment on this post by the beginning of class on April 13, 2017.
Leave a post about your group project:
What is the subject of your group project?
Which of your fellow […] - Load More