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  • Information Visualization
The Beauty of Data Visualization
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David McCandless turns complex data sets (like worldwide military spending, media buzz, Facebook status updates) into beautiful, simple diagrams that tease out unseen patterns and connections. Good design, he suggests, is the best way to navigate information glut -- and it may just change the way we see the world. A quiz, thought provoking question, and links for further study are provided to create a lesson around the 18-minute video. Educators may use the platform to easily "Flip" or create their own lesson for use with their students of any age or level.

Subject:
Journalism
Material Type:
Lecture
Provider:
TED
Provider Set:
TED-Ed
Author:
David McCandless
Date Added:
08/23/2010
Data Analysis: Take it to the MAX
Conditions of Use:
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This course is for all of those struggling with data analysis. That crazy data collection from your boss? Megabytes of sensor data to analyze? Looking for a smart way visualize your data in order to make sense out of it? We’ve got you covered!

Using video lectures and hands-on exercises, we will teach you cutting-edge techniques and best practices that will boost your data analysis and visualization skills.

This course has been awarded with the Wharton-QS gold education award in the category Regional awards Europe.
We will take a deep dive into data analysis with spreadsheets: PivotTables, VLOOKUPS, Named ranges, what-if analyses, making great graphs – all those will be covered in the first weeks of the course. After that, we will investigate the quality of the spreadsheet model, and especially how to make sure your spreadsheet remains error-free and robust.

Finally, once we have mastered spreadsheets, we will demonstrate other ways to store and analyze data. We will also look into how Python, a programming language, can help us with analyzing and manipulating data in spreadsheets.

This course is created using Excel 2013 and Windows. Most assignments can be made using another spreadsheet program and operating system as well, but we cannot offer full support for all configurations.

Subject:
Engineering
Material Type:
Full Course
Provider:
Delft University of Technology
Provider Set:
Delft University OpenCourseWare
Author:
Dr. Felienne Hermans
Date Added:
08/01/2018
Data Analysis: Building your own Business Dashboard
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Are you ready to leave the sandbox and go for the real deal? Have you followed Data Analysis: Take It to the MAX() and Data Analysis: Visualization and Dashboard Design and are ready to carry out more robust data analysis?

In this project-based course you will engage in a real data analysis project that simulates the complexity and challenges of data analysts at work. Testing, data wrangling, Pivot Tables, sparklines? Now that you have mastered them you are ready to apply them all and carry out an independent data analysis.

For your project, you will pick one raw dataset out of several options, which you will turn into a dashboard. You will begin with a business question that is related to the dataset that you choose. The datasets will touch upon different business domains, such as revenue management, call-center management, investment, etc.

Subject:
Engineering
Measurement and Data
Material Type:
Full Course
Provider:
Delft University of Technology
Provider Set:
Delft University OpenCourseWare
Author:
Dr. Felienne Hermans
Date Added:
07/31/2018
Statistical Thinking and Data Analysis, Fall 2011
Conditions of Use:
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This course is an introduction to statistical data analysis. Topics are chosen from applied probability, sampling, estimation, hypothesis testing, linear regression, analysis of variance, categorical data analysis, and nonparametric statistics.

Subject:
Statistics and Probability
Material Type:
Full Course
Provider:
M.I.T.
Provider Set:
M.I.T. OpenCourseWare
Author:
Allison Chang
Cynthia Rudin
Dimitrios Bisias
Date Added:
01/01/2011
Statistics and Visualization for Data Analysis and Inference, January IAP 2009
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A whirl-wind tour of the statistics used in behavioral science research, covering topics including: data visualization, building your own null-hypothesis distribution through permutation, useful parametric distributions, the generalized linear model, and model-based analyses more generally. Familiarity with MATLABA, Octave, or R will be useful, prior experience with statistics will be helpful but is not essential. This course is intended to be a ground-up sketch of a coherent, alternative perspective to the "null-hypothesis significance testing" method for behavioral research (but don't worry if you don't know what this means).

Subject:
Statistics and Probability
Material Type:
Full Course
Provider:
M.I.T.
Provider Set:
M.I.T. OpenCourseWare
Author:
Frank, Mike
Vul, Ed
Date Added:
01/01/2009
Data Analysis: Coin Flipping
Conditions of Use:
Read the Fine Print
Rating

Using two different coins and recording the results of both coins helps students dispel this initial misconception as they analyze the graph results. Class discussion should focus on analyzing the data to determine if the game is fair or not. Directions and gameboard are included in the download.

Material Type:
Game
Provider:
Mathwire
Author:
Terry Kawas
Date Added:
02/16/2011
Data Analysis and Probability Games
Conditions of Use:
Read the Fine Print
Rating

These activities support students as they conceptually develop a sense of how probability affects the outcome of games. Students will find that applying their knowledge of probability will help them win some of the games

Material Type:
Game
Provider:
Mathwire
Author:
Terry Kawas
Date Added:
02/16/2011
OER-UCLouvain: LPHY2131 data analysis lab using CMS open data
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This assembles material for the LPHY2131 data analysis lab at UCLouvain. The documentation covers the three sessions of the laboratory and provides some additional information. The results that are obtained in this lab can be compared to the published cross-section measurement for the Z and W at the LHC, at 7TeV, by the CMS collaboration: Measurement of the Inclusive W and Z Production Cross Sections in pp Collisions at sqrt(s) = 7 TeV

Subject:
Physical Science
Material Type:
Lecture Notes
Provider:
OER-UCLOUVAIN
Author:
DELAERE Christophe
Date Added:
03/23/2018
Qualitative Data Analysis
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This course emphasizes the analysis of ethnographic and other forms of qualitative data in public health research. We introduce various interpretive analytic approaches, explore their use, and guide students in applying them to data. We also introduce the use of computer software for coding textual data (Atlas.ti). Students analyze data they have collected as part of fieldwork projects initiated in 410.690 and write up the results in a final paper. Classroom sessions include lectures, discussions, intensive group work related to the fieldwork projects, and instruction in the computer lab.

Subject:
Health, Medicine and Nursing
Material Type:
Full Course
Homework/Assignment
Lecture Notes
Reading
Syllabus
Provider:
Johns Hopkins Bloomberg School of Public Health
Provider Set:
JHSPH OpenCourseWare
Author:
Katherine Fritz
Date Added:
01/15/2008
Data Analysis
Conditions of Use:
Remix and Share
Rating

The applet in this section allows for simple data analysis of univariate data. Users can either generate normal or uniform data for k samples or copy and paste data from another source to a text box. A univariate analysis is performed for all k samples.

Subject:
Statistics and Probability
Material Type:
Activity/Lab
Provider:
Consortium for the Advancement of Undergraduate Statistics Education
Provider Set:
Causeweb.org
Author:
C. Anderson-Cook, S. Dorai-Raj, T. Robinson, Virginia Tech Department of Statistics
Date Added:
02/16/2011
Radio JOVE Data Analysis
Conditions of Use:
Read the Fine Print
Rating

The objectives of this lesson are to understand the characteristics of the data that is collected using the Radio JOVE antenna/receiver system. Using calibrations for the equipment, one can determine a proper measure of the peak intensity of the output, identify the duration of the solar or Jovian radio activity, and calculate the approximate total power emitted by the source. Master these concepts by completing example problems.

Subject:
Physics
Material Type:
Lesson Plan
Provider:
NASA
Date Added:
02/16/2011
Data Carpentry: R for data analysis and visualization of Ecological Data
Conditions of Use:
No Strings Attached
Rating

This is an introduction to R designed for participants with no programming experience. These lessons can be taught in a day. They start with some basic information about R syntax, the RStudio interface, and move through how to import CSV files, the structure of data frames, how to deal with factors, how to add/remove rows and columns, and finish with how to calculate summary statistics for each level and a very brief introduction to plotting.

Subject:
Computer Science
Material Type:
Lesson
Provider:
NumFocus
Provider Set:
Data Carpentry Ecology Materials
Author:
Auriel Fournier
François Michonneau
Date Added:
03/20/2017
IHME: Data Visualizations
Rating

Institute for Health Metrics and Evaluation (IHME) strives to make its data freely and easily accessible and to provide innovative ways to visualize complex topics. Our data visualizations allow you to see patterns and follow trends that are not readily apparent in the numbers themselves. Here you can watch how trends in mortality change over time, choose countries to compare progress in a variety of health areas, or see how countries compare against each other on a global map.

Subject:
Information Science
Material Type:
Lesson
Provider:
TeachingWithData.org
Provider Set:
TeachingWithData.org
Author:
IHME
Date Added:
11/07/2014
Understanding the Air through Data Analysis
Conditions of Use:
Read the Fine Print
Rating

Students build on their existing air quality knowledge and a description of a data set to each develop a hypothesis around how and why air pollutants vary on a daily and seasonal basis. Then they are guided by a worksheet through an Excel-based analysis of the data. This includes entering formulas to calculate statistics and creating plots of the data. As students complete each phase of the analysis, reflection questions guide their understanding of what new information the analysis reveals. At activity end, students evaluate their original hypotheses and “put all of the pieces together.” The activity includes one carbon dioxide worksheet/data set and one ozone worksheet/data set; providing students and/or instructors with a content option. The activity also serves as a good standalone introduction to using Excel.

Subject:
Atmospheric Science
Material Type:
Activity/Lab
Provider:
TeachEngineering
Provider Set:
TeachEngineering
Author:
Ashley Collier
Ben Graves
Daniel Knight
Drew Meyers
Eric Ambos
Eric Lee
Erik Hotaling
Hanadi Adel Salamah
Joanna Gordon
Katya Hafich
Michael Hannigan
Nicholas VanderKolk
Olivia Cecil
Victoria Danner
Date Added:
02/17/2017
Data Analysis: Visualization and Dashboard Design
Conditions of Use:
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Struggling with data at work? Wasting valuable time working in multiple spreadsheets to gain an overview of your business? Find it hard to gain sharp insights from piles of data on your desktop?

If you are looking to enhance your efficiency in the office and improve your performance by making sense of data faster and smarter, then this advanced data analysis course is for you.

If you have already sharpened your spreadsheet skills in Data Analysis: Take It to the MAX(), this course will help you dig deeper. You will learn advanced techniques for robust data analysis in a business environment. This course covers the main tasks required from data analysts today, including importing, summarizing, interpreting, analyzing and visualizing data. It aims to equip you with the tools that will enable you to be an independent data analyst. Most techniques will be taught in Excel with add-ons and free tools available online. We encourage you to use your own data in this course but if not available, the course team can provide.

These course materials are part of an online course of TU Delft. Do you want to experience an active exchange of information between academic staff and students? Then join the community of online learners and enroll in this MOOC. This course is part of the Data Analysis XSeries.

Subject:
Engineering
Business and Communication
Material Type:
Full Course
Provider:
Delft University of Technology
Provider Set:
Delft University OpenCourseWare
Author:
Dr. Felienne Hermans
Date Added:
08/01/2018
How to Process, Analyze and Visualize Data, January IAP 2012
Conditions of Use:
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This course is an introduction to data cleaning, analysis and visualization. We will teach the basics of data analysis through concrete examples. You will learn how to take raw data, extract meaningful information, use statistical tools, and make visualizations. This was offered as a non-credit course during the Independent Activities Period (IAP), which is a special 4-week term at MIT that runs from the first week of January until the end of the month.

Subject:
Statistics and Probability
Material Type:
Full Course
Provider:
M.I.T.
Provider Set:
M.I.T. OpenCourseWare
Author:
Adam Marcus
Eugene Wu
Date Added:
01/01/2012
Artificial Intelligence
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An quick overview of AI from both the technical and the philosophical points of view. Topics discussed include search, A*, Knowledge Representation, Neural Nets. Video of each class is available, as are problem sets.

Subject:
Computer Science
Material Type:
Full Course
Homework/Assignment
Lecture
Reading
Syllabus
Provider:
ArsDigita University
Provider Set:
ArsDigita University
Author:
Patrick Winston
Date Added:
02/16/2011
Integrating Science and Math: Weather and Data Analysis
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This article discusses how the study of weather can meet the NCTM Data Analysis and Probability standard. Links to lessons for grades K-2 and 3-5 are provided.

Subject:
Environmental Science
Material Type:
Lesson Plan
Provider:
Ohio State University College of Education and Human Ecology
Provider Set:
Beyond Penguins and Polar Bears: An Online Magazine for K-5 Teachers
Author:
Jessica Fries-Gaither
Date Added:
10/17/2014
Using Google Forms and Spreadsheets
Conditions of Use:
Read the Fine Print
Rating

In this KQED video tutorial learn about Google forms and spreadsheets, Google Drive tools for collecting, organizing and visualizing data. ***Access to Teacher's Domain content now requires free login to PBS Learning Media.

Subject:
Arts and Humanities
Material Type:
Lecture
Provider:
PBS
Provider Set:
PBS Learning Media Teacher's Domain
Date Added:
06/25/2014
Programming with MATLAB
Conditions of Use:
No Strings Attached
Rating

The best way to learn how to program is to do something useful, so this introduction to MATLAB is built around a common scientific task: data analysis. Our real goal isn’t to teach you MATLAB, but to teach you the basic concepts that all programming depends on. 

Subject:
Computer Science
Material Type:
Lesson
Provider:
NumFocus
Provider Set:
Software Carpentry
Author:
Ashwin Srinath
Isabell Kiral-Kornek
Date Added:
03/20/2017