23 classes matched your search criteria.
PA 5929 is also offered in Spring 2024
PA 5929 is also offered in Fall 2023
PA 5929 is also offered in Spring 2023
PA 5929 is also offered in Fall 2022
PA 5929 is also offered in Spring 2022
PA 5929 is also offered in Fall 2021
PA 5929 is also offered in Spring 2021
PA 5929 is also offered in Fall 2020
Spring 2024 | PA 5929 Section 001: Data Visualization: Telling Stories with Numbers (57218)
- Instructor(s)
- Class Component:
- Laboratory
- Credits:
- 2 Credits
- Grading Basis:
- Student Option
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- In Person
- Class Attributes:
- Online Course
- Enrollment Requirements:
- Graduate Student
- Times and Locations:
- First Half of Term01/16/2024 - 03/11/2024Tue, Thu 02:30PM - 03:45PMUMTC, West BankHubert H Humphrey Center 8502/03/2024Sat 01:00PM - 04:00PMUMTC, West BankHubert H Humphrey Center 85
- Enrollment Status:
- Open (0 of 32 seats filled)
- Also Offered:
- Course Catalog Description:
- Tools for communicating quantitative information in an intelligent, effective and persuasive way. Topics covered include 1) writing and speaking about data; 2) data management in Excel in order to prepare data for charting; 3) understanding and ability to deploy core concepts in of design, layout, typography and color to maximize the impact of their data visualizations 4) determining which types of statistical measures are most effective for each type of data and message; 5) determining which types of design to use for communicating quantitative information; and 6) designing graphs and tables that are intelligent and compelling for communicating quantitative information.
- Class Notes:
- http://classinfo.umn.edu/?dorelien+PA5929+Spring2024
- Class Description:
- The class will have a practical approach, combining discussion and practical exercises. The course is designed to be like a walk-through, starting from collecting and organizing data and ending with advanced graph designs.The course in the spring will use Excel and Tableau. There will be additional modules available for more advance Excel users and those who want to go beyond the basics in Tableau. I will not teach R as part of the class but will make available the R modules and handouts for students that are interested in learning R.
- Learning Objectives:
- Learn to make better tables- see example below
Learn to make better figures
- Grading:
- Please note that it is possible to audit the course or take the course S/N. I encourage students that are already taking a full load of classes to sign up for this class S/N, that way you can focus on learning the material and not on the letter grade.
4 Problem Sets (each problem set is worth 15% of final grade). The problem sets will be due one week after being assigned and will need to be uploaded to Canvas before the start of class.If you are satisfied with your grades from the first 3 assignments, you do not have to turn in assignment 4. If you are not, you should turn in assignment 4 and I will drop the lowest of your assignment grades.
1 Final Report (40% of final grade) - Class Format:
- Meets twice a week for first half the semester. The majority of class time is spent doing in-class exercises.
Modifications for online mode
The fall 2021 class will be taught online while the two spring semester sessions will be in person. The motivation is to accommodate students who are not able to be vaccinated or who would otherwise have trouble making it to an in-person session of the class.- This will be a live synchronous class. All classes will be recorded, and recordings will be posted the next day.
- During the in-class exercise portion of the class, two break-out rooms will be created. One breakout room is for advanced students who wish to go at their own pace and not follow along with the professor. The second breakout room is a place that students who need extra help can go to quickly get help from the TA and then rejoin the main room.
- Textbooks:
- https://bookstores.umn.edu/course-lookup/57218/1243
- Past Syllabi:
- http://classinfo.umn.edu/syllabi/dorelien_PA5929_Spring2019.pdf (Spring 2019)
- Instructor Supplied Information Last Updated:
- 8 May 2021
Spring 2024 | PA 5929 Section 002: Data Visualization: Telling Stories with Numbers (65722)
- Instructor(s)
- Class Component:
- Laboratory
- Credits:
- 2 Credits
- Grading Basis:
- Student Option
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- In Person
- Class Attributes:
- Online Course
- Enrollment Requirements:
- Graduate Student
- Times and Locations:
- Second Half of Term03/12/2024 - 04/29/2024Tue, Thu 04:00PM - 05:15PMUMTC, West BankHubert H Humphrey Center 8503/30/2024Sat 01:00PM - 04:00PMUMTC, West BankHubert H Humphrey Center 85
- Enrollment Status:
- Open (0 of 32 seats filled)
- Also Offered:
- Course Catalog Description:
- Tools for communicating quantitative information in an intelligent, effective and persuasive way. Topics covered include 1) writing and speaking about data; 2) data management in Excel in order to prepare data for charting; 3) understanding and ability to deploy core concepts in of design, layout, typography and color to maximize the impact of their data visualizations 4) determining which types of statistical measures are most effective for each type of data and message; 5) determining which types of design to use for communicating quantitative information; and 6) designing graphs and tables that are intelligent and compelling for communicating quantitative information.
- Class Notes:
- http://classinfo.umn.edu/?dorelien+PA5929+Spring2024
- Class Description:
- The class will have a practical approach, combining discussion and practical exercises. The course is designed to be like a walk-through, starting from collecting and organizing data and ending with advanced graph designs.The course in the spring will use Excel and Tableau. There will be additional modules available for more advance Excel users and those who want to go beyond the basics in Tableau. I will not teach R as part of the class but will make available the R modules and handouts for students that are interested in learning R.
- Learning Objectives:
- Learn to make better tables- see example below Learn to make better figures
- Grading:
- Please note that it is possible to audit the course or take the course S/N. I encourage students that are already taking a full load of classes to sign up for this class S/N, that way you can focus on learning the material and not on the letter grade.
4 Problem Sets (each problem set is worth 15% of final grade). The problem sets will be due one week after being assigned and will need to be uploaded to Canvas before the start of class.If you are satisfied with your grades from the first 3 assignments, you do not have to turn in assignment 4. If you are not, you should turn in assignment 4 and I will drop the lowest of your assignment grades.
1 Final Report (40% of final grade) - Class Format:
- Meets twice a week for first half the semester. The majority of class time is spent doing in-class exercises.
Modifications for online mode
The fall 2021 class will be taught online while the two spring semester sessions will be in person. The motivation is to accommodate students who are not able to be vaccinated or who would otherwise have trouble making it to an in-person session of the class.- This will be a live synchronous class. All classes will be recorded, and recordings will be posted the next day.
- During the in-class exercise portion of the class, two break-out rooms will be created. One breakout room is for advanced students who wish to go at their own pace and not follow along with the professor. The second breakout room is a place that students who need extra help can go to quickly get help from the TA and then rejoin the main room.
- Textbooks:
- https://bookstores.umn.edu/course-lookup/65722/1243
- Past Syllabi:
- http://classinfo.umn.edu/syllabi/dorelien_PA5929_Spring2019.pdf (Spring 2019)
- Instructor Supplied Information Last Updated:
- 8 May 2021
Fall 2023 | PA 5929 Section 001: Data Visualization: Telling Stories with Numbers (23342)
- Instructor(s)
- Class Component:
- Laboratory
- Credits:
- 2 Credits
- Grading Basis:
- Student Option
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- In Person
- Class Attributes:
- Online Course
- Enrollment Requirements:
- Graduate Student
- Times and Locations:
- Regular Academic Session09/05/2023 - 12/13/2023Wed 04:00PM - 05:40PMUMTC, West BankHubert H Humphrey Center 85
- Enrollment Status:
- Open (31 of 32 seats filled)
- Also Offered:
- Course Catalog Description:
- Tools for communicating quantitative information in an intelligent, effective and persuasive way. Topics covered include 1) writing and speaking about data; 2) data management in Excel in order to prepare data for charting; 3) understanding and ability to deploy core concepts in of design, layout, typography and color to maximize the impact of their data visualizations 4) determining which types of statistical measures are most effective for each type of data and message; 5) determining which types of design to use for communicating quantitative information; and 6) designing graphs and tables that are intelligent and compelling for communicating quantitative information.
- Class Notes:
- http://classinfo.umn.edu/?maas0021+PA5929+Fall2023
- Class Description:
- This course will teach students how to organize and present data in the most effective way. Lectures will explore theories and elements of graphs and tables design, more specifically with how to create and organize tables and data. The central goal is to provide students with the tools for communicating information in an intelligent, effective and persuasive way.
- Who Should Take This Class?:
- Students interested in efficiently and effectively communicating data visually.
- Learning Objectives:
- Develop a firm understanding of the role of design, color, composition, type and statistical rigor in effectively communicating data visually.
- Grading:
- 15% class attendance and completion of in-class exercises
70% series of six assignments
15% final project - Exam Format:
- No exams
- Class Format:
- This class will combine lecture, in-class critique of data visualization approaches and discussion, and practical lab exercises and assignments. Classes will begin with a lecture to introduce topics to be explored and discussed. Hands-on work with the software will also be emphasized to allow students to complete the assignments and relate their skills to their own research interests.
- Workload:
- Weekly lectures including critique of data visualizations, in-class labs each week to help students gain familiarity with the tools and weekly assignments. Students will work with and become familiar with the core visualization functions in Microsoft Excel, Adobe Illustrator, Tableau and R.
- Textbooks:
- https://bookstores.umn.edu/course-lookup/23342/1239
- Past Syllabi:
- http://classinfo.umn.edu/syllabi/maas0021_PA5929_Fall2018.docx (Fall 2018)
http://classinfo.umn.edu/syllabi/maas0021_PA5929_Spring2018.pdf (Spring 2018) - Instructor Supplied Information Last Updated:
- 30 December 2019
Spring 2023 | PA 5929 Section 001: Data Visualization: Telling Stories with Numbers (57593)
- Instructor(s)
- Class Component:
- Laboratory
- Credits:
- 2 Credits
- Grading Basis:
- Student Option
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- In Person
- Class Attributes:
- Online Course
- Enrollment Requirements:
- Graduate Student
- Times and Locations:
- First Half of Term01/17/2023 - 03/13/2023Tue, Thu 02:30PM - 03:45PMUMTC, West BankHubert H Humphrey Center 8502/04/2023Sat 01:00PM - 04:00PMUMTC, West BankHubert H Humphrey Center 85
- Enrollment Status:
- Closed (32 of 32 seats filled)
- Also Offered:
- Course Catalog Description:
- Tools for communicating quantitative information in an intelligent, effective and persuasive way. Topics covered include 1) writing and speaking about data; 2) data management in Excel in order to prepare data for charting; 3) understanding and ability to deploy core concepts in of design, layout, typography and color to maximize the impact of their data visualizations 4) determining which types of statistical measures are most effective for each type of data and message; 5) determining which types of design to use for communicating quantitative information; and 6) designing graphs and tables that are intelligent and compelling for communicating quantitative information.
- Class Notes:
- http://classinfo.umn.edu/?maas0021+PA5929+Spring2023
- Class Description:
- This course will teach students how to organize and present data in the most effective way. Lectures will explore theories and elements of graphs and tables design, more specifically with how to create and organize tables and data. The central goal is to provide students with the tools for communicating information in an intelligent, effective and persuasive way.
- Who Should Take This Class?:
- Students interested in efficiently and effectively communicating data visually.
- Learning Objectives:
- Develop a firm understanding of the role of design, color, composition, type and statistical rigor in effectively communicating data visually.
- Grading:
- 15% class attendance and completion of in-class exercises
70% series of six assignments
15% final project - Exam Format:
- No exams
- Class Format:
- This class will combine lecture, in-class critique of data visualization approaches and discussion, and practical lab exercises and assignments. Classes will begin with a lecture to introduce topics to be explored and discussed. Hands-on work with the software will also be emphasized to allow students to complete the assignments and relate their skills to their own research interests.
- Workload:
- Weekly lectures including critique of data visualizations, in-class labs each week to help students gain familiarity with the tools and weekly assignments. Students will work with and become familiar with the core visualization functions in Microsoft Excel, Adobe Illustrator, Tableau and R.
- Textbooks:
- https://bookstores.umn.edu/course-lookup/57593/1233
- Past Syllabi:
- http://classinfo.umn.edu/syllabi/maas0021_PA5929_Fall2018.docx (Fall 2018)
http://classinfo.umn.edu/syllabi/maas0021_PA5929_Spring2018.pdf (Spring 2018) - Instructor Supplied Information Last Updated:
- 30 December 2019
Spring 2023 | PA 5929 Section 002: Data Visualization: Telling Stories with Numbers (57597)
- Instructor(s)
- Class Component:
- Laboratory
- Credits:
- 2 Credits
- Grading Basis:
- Student Option
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- Completely Online
- Class Attributes:
- Online Course
- Enrollment Requirements:
- Graduate Student
- Times and Locations:
- Second Half of Term03/14/2023 - 05/01/2023Tue, Thu 04:00PM - 05:15PMOff CampusUMN REMOTE04/01/2023Sat 01:00PM - 04:00PMOff CampusUMN REMOTE
- Enrollment Status:
- Closed (36 of 36 seats filled)
- Also Offered:
- Course Catalog Description:
- Tools for communicating quantitative information in an intelligent, effective and persuasive way. Topics covered include 1) writing and speaking about data; 2) data management in Excel in order to prepare data for charting; 3) understanding and ability to deploy core concepts in of design, layout, typography and color to maximize the impact of their data visualizations 4) determining which types of statistical measures are most effective for each type of data and message; 5) determining which types of design to use for communicating quantitative information; and 6) designing graphs and tables that are intelligent and compelling for communicating quantitative information.
- Class Notes:
- This class will be held REMOTELY (synchronously online). HHH 85 will be available for students to use, if desired http://classinfo.umn.edu/?maas0021+PA5929+Spring2023
- Class Description:
- This course will teach students how to organize and present data in the most effective way. Lectures will explore theories and elements of graphs and tables design, more specifically with how to create and organize tables and data. The central goal is to provide students with the tools for communicating information in an intelligent, effective and persuasive way.
- Who Should Take This Class?:
- Students interested in efficiently and effectively communicating data visually.
- Learning Objectives:
- Develop a firm understanding of the role of design, color, composition, type and statistical rigor in effectively communicating data visually.
- Grading:
- 15% class attendance and completion of in-class exercises
70% series of six assignments
15% final project - Exam Format:
- No exams
- Class Format:
- This class will combine lecture, in-class critique of data visualization approaches and discussion, and practical lab exercises and assignments. Classes will begin with a lecture to introduce topics to be explored and discussed. Hands-on work with the software will also be emphasized to allow students to complete the assignments and relate their skills to their own research interests.
- Workload:
- Weekly lectures including critique of data visualizations, in-class labs each week to help students gain familiarity with the tools and weekly assignments. Students will work with and become familiar with the core visualization functions in Microsoft Excel, Adobe Illustrator, Tableau and R.
- Textbooks:
- https://bookstores.umn.edu/course-lookup/57597/1233
- Past Syllabi:
- http://classinfo.umn.edu/syllabi/maas0021_PA5929_Fall2018.docx (Fall 2018)
http://classinfo.umn.edu/syllabi/maas0021_PA5929_Spring2018.pdf (Spring 2018) - Instructor Supplied Information Last Updated:
- 30 December 2019
Fall 2022 | PA 5929 Section 001: Data Visualization: Telling Stories with Numbers (23797)
- Instructor(s)
- Class Component:
- Laboratory
- Credits:
- 2 Credits
- Grading Basis:
- Student Option
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- In Person
- Class Attributes:
- Online Course
- Enrollment Requirements:
- Graduate Student
- Times and Locations:
- First Half of Term09/06/2022 - 10/24/2022Tue, Thu 04:00PM - 05:15PMUMTC, West BankHubert H Humphrey Center 8509/24/2022Sat 01:00PM - 04:00PMUMTC, West BankHubert H Humphrey Center 85
- Enrollment Status:
- Open (31 of 32 seats filled)
- Also Offered:
- Course Catalog Description:
- Tools for communicating quantitative information in an intelligent, effective and persuasive way. Topics covered include 1) writing and speaking about data; 2) data management in Excel in order to prepare data for charting; 3) understanding and ability to deploy core concepts in of design, layout, typography and color to maximize the impact of their data visualizations 4) determining which types of statistical measures are most effective for each type of data and message; 5) determining which types of design to use for communicating quantitative information; and 6) designing graphs and tables that are intelligent and compelling for communicating quantitative information.
- Class Notes:
- http://classinfo.umn.edu/?dorelien+PA5929+Fall2022
- Class Description:
- The class will have a practical approach, combining discussion and practical exercises. The course is designed to be like a walk-through, starting from collecting and organizing data and ending with advanced graph designs.The course in the spring will use Excel and Tableau. There will be additional modules available for more advance Excel users and those who want to go beyond the basics in Tableau. I will not teach R as part of the class but will make available the R modules and handouts for students that are interested in learning R.
- Learning Objectives:
- Learn to make better tables- see example below Learn to make better figures
- Grading:
- Please note that it is possible to audit the course or take the course S/N. I encourage students that are already taking a full load of classes to sign up for this class S/N, that way you can focus on learning the material and not on the letter grade.
4 Problem Sets (each problem set is worth 15% of final grade). The problem sets will be due one week after being assigned and will need to be uploaded to Canvas before the start of class.If you are satisfied with your grades from the first 3 assignments, you do not have to turn in assignment 4. If you are not, you should turn in assignment 4 and I will drop the lowest of your assignment grades.
1 Final Report (40% of final grade) - Class Format:
- Meets twice a week for first half the semester. The majority of class time is spent doing in-class exercises.
Modifications for online mode
The fall 2021 class will be taught online while the two spring semester sessions will be in person. The motivation is to accommodate students who are not able to be vaccinated or who would otherwise have trouble making it to an in-person session of the class.- This will be a live synchronous class. All classes will be recorded, and recordings will be posted the next day.
- During the in-class exercise portion of the class, two break-out rooms will be created. One breakout room is for advanced students who wish to go at their own pace and not follow along with the professor. The second breakout room is a place that students who need extra help can go to quickly get help from the TA and then rejoin the main room.
- Textbooks:
- https://bookstores.umn.edu/course-lookup/23797/1229
- Past Syllabi:
- http://classinfo.umn.edu/syllabi/dorelien_PA5929_Spring2019.pdf (Spring 2019)
- Instructor Supplied Information Last Updated:
- 8 May 2021
Spring 2022 | PA 5929 Section 001: Data Visualization: Telling Stories with Numbers (58966)
- Instructor(s)
- Class Component:
- Laboratory
- Credits:
- 2 Credits
- Grading Basis:
- Student Option
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- In Person Term Based
- Class Attributes:
- Online Course
- Enrollment Requirements:
- Graduate Student
- Times and Locations:
- First Half of Term01/18/2022 - 03/14/2022Tue, Thu 02:30PM - 03:45PMUMTC, West BankHubert H Humphrey Center 8502/05/2022Sat 01:00PM - 04:00PMUMTC, West BankHubert H Humphrey Center 85
- Enrollment Status:
- Open (26 of 29 seats filled)
- Also Offered:
- Course Catalog Description:
- Tools for communicating quantitative information in an intelligent, effective and persuasive way. Topics covered include 1) writing and speaking about data; 2) data management in Excel in order to prepare data for charting; 3) understanding and ability to deploy core concepts in of design, layout, typography and color to maximize the impact of their data visualizations 4) determining which types of statistical measures are most effective for each type of data and message; 5) determining which types of design to use for communicating quantitative information; and 6) designing graphs and tables that are intelligent and compelling for communicating quantitative information.
- Class Notes:
- http://classinfo.umn.edu/?dorelien+PA5929+Spring2022
- Class Description:
- The class will have a practical approach, combining discussion and practical exercises. The course is designed to be like a walk-through, starting from collecting and organizing data and ending with advanced graph designs.The course in the spring will use Excel and Tableau. There will be additional modules available for more advance Excel users and those who want to go beyond the basics in Tableau. I will not teach R as part of the class but will make available the R modules and handouts for students that are interested in learning R.
- Learning Objectives:
- Learn to make better tables- see example below Learn to make better figures
- Grading:
- Please note that it is possible to audit the course or take the course S/N. I encourage students that are already taking a full load of classes to sign up for this class S/N, that way you can focus on learning the material and not on the letter grade.
4 Problem Sets (each problem set is worth 15% of final grade). The problem sets will be due one week after being assigned and will need to be uploaded to Canvas before the start of class.If you are satisfied with your grades from the first 3 assignments, you do not have to turn in assignment 4. If you are not, you should turn in assignment 4 and I will drop the lowest of your assignment grades.
1 Final Report (40% of final grade) - Class Format:
- Meets twice a week for first half the semester. The majority of class time is spent doing in-class exercises.
Modifications for online mode
The fall 2021 class will be taught online while the two spring semester sessions will be in person. The motivation is to accommodate students who are not able to be vaccinated or who would otherwise have trouble making it to an in-person session of the class.- This will be a live synchronous class. All classes will be recorded, and recordings will be posted the next day.
- During the in-class exercise portion of the class, two break-out rooms will be created. One breakout room is for advanced students who wish to go at their own pace and not follow along with the professor. The second breakout room is a place that students who need extra help can go to quickly get help from the TA and then rejoin the main room.
- Textbooks:
- https://bookstores.umn.edu/course-lookup/58966/1223
- Past Syllabi:
- http://classinfo.umn.edu/syllabi/dorelien_PA5929_Spring2019.pdf (Spring 2019)
- Instructor Supplied Information Last Updated:
- 8 May 2021
Spring 2022 | PA 5929 Section 002: Data Visualization: Telling Stories with Numbers (58976)
- Instructor(s)
- Class Component:
- Laboratory
- Credits:
- 2 Credits
- Grading Basis:
- Student Option
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- Completely Online
- Class Attributes:
- Online Course
- Enrollment Requirements:
- Graduate Student
- Times and Locations:
- Second Half of Term03/15/2022 - 05/02/2022Tue, Thu 04:00PM - 05:15PMOff CampusUMN REMOTE04/02/2022Sat 01:00PM - 04:00PMOff CampusUMN REMOTE
- Enrollment Status:
- Open (30 of 32 seats filled)
- Also Offered:
- Course Catalog Description:
- Tools for communicating quantitative information in an intelligent, effective and persuasive way. Topics covered include 1) writing and speaking about data; 2) data management in Excel in order to prepare data for charting; 3) understanding and ability to deploy core concepts in of design, layout, typography and color to maximize the impact of their data visualizations 4) determining which types of statistical measures are most effective for each type of data and message; 5) determining which types of design to use for communicating quantitative information; and 6) designing graphs and tables that are intelligent and compelling for communicating quantitative information.
- Class Notes:
- Class will be REMOTE (synchronously online during the scheduled class time). http://classinfo.umn.edu/?dorelien+PA5929+Spring2022
- Class Description:
- The class will have a practical approach, combining discussion and practical exercises. The course is designed to be like a walk-through, starting from collecting and organizing data and ending with advanced graph designs.The course in the spring will use Excel and Tableau. There will be additional modules available for more advance Excel users and those who want to go beyond the basics in Tableau. I will not teach R as part of the class but will make available the R modules and handouts for students that are interested in learning R.
- Learning Objectives:
- Learn to make better tables- see example below Learn to make better figures
- Grading:
- Please note that it is possible to audit the course or take the course S/N. I encourage students that are already taking a full load of classes to sign up for this class S/N, that way you can focus on learning the material and not on the letter grade.
4 Problem Sets (each problem set is worth 15% of final grade). The problem sets will be due one week after being assigned and will need to be uploaded to Canvas before the start of class.If you are satisfied with your grades from the first 3 assignments, you do not have to turn in assignment 4. If you are not, you should turn in assignment 4 and I will drop the lowest of your assignment grades.
1 Final Report (40% of final grade) - Class Format:
- Meets twice a week for first half the semester. The majority of class time is spent doing in-class exercises.
Modifications for online mode
The fall 2021 class will be taught online while the two spring semester sessions will be in person. The motivation is to accommodate students who are not able to be vaccinated or who would otherwise have trouble making it to an in-person session of the class.- This will be a live synchronous class. All classes will be recorded, and recordings will be posted the next day.
- During the in-class exercise portion of the class, two break-out rooms will be created. One breakout room is for advanced students who wish to go at their own pace and not follow along with the professor. The second breakout room is a place that students who need extra help can go to quickly get help from the TA and then rejoin the main room.
- Textbooks:
- https://bookstores.umn.edu/course-lookup/58976/1223
- Past Syllabi:
- http://classinfo.umn.edu/syllabi/dorelien_PA5929_Spring2019.pdf (Spring 2019)
- Instructor Supplied Information Last Updated:
- 8 May 2021
Fall 2021 | PA 5929 Section 001: Data Visualization: Telling Stories with Numbers (25829)
- Instructor(s)
- Class Component:
- Laboratory
- Credits:
- 2 Credits
- Grading Basis:
- Student Option
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- Completely Online
- Class Attributes:
- Online Course
- Enrollment Requirements:
- Graduate Student
- Times and Locations:
- First Half of Term09/07/2021 - 10/25/2021Tue, Thu 04:00PM - 05:15PMOff CampusUMN REMOTE09/25/2021Sat 01:00PM - 04:00PMOff CampusUMN REMOTE
- Enrollment Status:
- Open (40 of 41 seats filled)
- Also Offered:
- Course Catalog Description:
- Tools for communicating quantitative information in an intelligent, effective and persuasive way. Topics covered include 1) writing and speaking about data; 2) data management in Excel in order to prepare data for charting; 3) understanding and ability to deploy core concepts in of design, layout, typography and color to maximize the impact of their data visualizations 4) determining which types of statistical measures are most effective for each type of data and message; 5) determining which types of design to use for communicating quantitative information; and 6) designing graphs and tables that are intelligent and compelling for communicating quantitative information.
- Class Notes:
- Class will be REMOTE (synchronously online during the scheduled time). http://classinfo.umn.edu/?dorelien+PA5929+Fall2021
- Class Description:
- The class will have a practical approach, combining discussion and practical exercises. The course is designed to be like a walk-through, starting from collecting and organizing data and ending with advanced graph designs.The course in the spring will use Excel and Tableau. There will be additional modules available for more advance Excel users and those who want to go beyond the basics in Tableau. I will not teach R as part of the class but will make available the R modules and handouts for students that are interested in learning R.
- Learning Objectives:
- Learn to make better tables- see example below Learn to make better figures
- Grading:
- Please note that it is possible to audit the course or take the course S/N. I encourage students that are already taking a full load of classes to sign up for this class S/N, that way you can focus on learning the material and not on the letter grade.
4 Problem Sets (each problem set is worth 15% of final grade). The problem sets will be due one week after being assigned and will need to be uploaded to Canvas before the start of class.If you are satisfied with your grades from the first 3 assignments, you do not have to turn in assignment 4. If you are not, you should turn in assignment 4 and I will drop the lowest of your assignment grades.
1 Final Report (40% of final grade) - Class Format:
- Meets twice a week for first half the semester. The majority of class time is spent doing in-class exercises.
Modifications for online mode
The fall 2021 class will be taught online while the two spring semester sessions will be in person. The motivation is to accommodate students who are not able to be vaccinated or who would otherwise have trouble making it to an in-person session of the class.- This will be a live synchronous class. All classes will be recorded, and recordings will be posted the next day.
- During the in-class exercise portion of the class, two break-out rooms will be created. One breakout room is for advanced students who wish to go at their own pace and not follow along with the professor. The second breakout room is a place that students who need extra help can go to quickly get help from the TA and then rejoin the main room.
- Textbooks:
- https://bookstores.umn.edu/course-lookup/25829/1219
- Past Syllabi:
- http://classinfo.umn.edu/syllabi/dorelien_PA5929_Spring2019.pdf (Spring 2019)
- Instructor Supplied Information Last Updated:
- 8 May 2021
Spring 2021 | PA 5929 Section 001: Data Visualization: Telling Stories with Numbers (54152)
- Instructor(s)
- Class Component:
- Laboratory
- Credits:
- 2 Credits
- Grading Basis:
- Student Option
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- Completely Online
- Class Attributes:
- Online Course
- Enrollment Requirements:
- Graduate Student
- Times and Locations:
- First Half of Term01/19/2021 - 03/08/2021Tue, Thu 02:30PM - 03:45PMOff CampusUMN REMOTE02/06/2021Sat 10:00AM - 01:00PMOff CampusUMN REMOTE
- Enrollment Status:
- Closed (35 of 34 seats filled)
- Also Offered:
- Course Catalog Description:
- Tools for communicating quantitative information in an intelligent, effective and persuasive way. Topics covered include 1) writing and speaking about data; 2) data management in Excel in order to prepare data for charting; 3) understanding and ability to deploy core concepts in of design, layout, typography and color to maximize the impact of their data visualizations 4) determining which types of statistical measures are most effective for each type of data and message; 5) determining which types of design to use for communicating quantitative information; and 6) designing graphs and tables that are intelligent and compelling for communicating quantitative information.
- Class Notes:
- Class will be offered REMOTELY. Class will meet synchronously-online during Spring 2021 during the scheduled time. http://classinfo.umn.edu/?dorelien+PA5929+Spring2021
- Class Description:
- The class will have a practical approach, combining discussion and practical exercises. The course is designed to be like a walk-through, starting from collecting and organizing data and ending with advanced graph designs.The course in the spring will use Excel and Tableau. There will be additional modules available for more advance Excel users and those who want to go beyond the basics in Tableau. I will not teach R as part of the class but will make available the R modules and handouts for students that are interested in learning R.
- Learning Objectives:
- Learn to make better tables- see example below Learn to make better figures
- Grading:
- Please note that it is possible to audit the course or take the course S/N. I encourage students that are already taking a full load of classes to sign up for this class S/N, that way you can focus on learning the material and not on the letter grade.4 Problem Sets (each problem set is worth 15% of final grade). The problem sets will be due one week after being assigned and will need to be uploaded to Moodle before the start of class.
1 Final Report (30% of final grade) - Class Format:
- Meets twice a week for first half the semester. The majority of class time is spent doing in-class exercises.
- Textbooks:
- https://bookstores.umn.edu/course-lookup/54152/1213
- Past Syllabi:
- http://classinfo.umn.edu/syllabi/dorelien_PA5929_Spring2019.pdf (Spring 2019)
- Instructor Supplied Information Last Updated:
- 9 November 2020
Spring 2021 | PA 5929 Section 002: Data Visualization: Telling Stories with Numbers (54163)
- Instructor(s)
- Class Component:
- Laboratory
- Credits:
- 2 Credits
- Grading Basis:
- Student Option
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- Completely Online
- Class Attributes:
- Online Course
- Enrollment Requirements:
- Graduate Student
- Times and Locations:
- Second Half of Term03/09/2021 - 05/03/2021Tue, Thu 04:00PM - 05:15PMOff CampusUMN REMOTE03/27/2021Sat 10:00AM - 01:00PMOff CampusUMN REMOTE
- Enrollment Status:
- Open (26 of 32 seats filled)
- Also Offered:
- Course Catalog Description:
- Tools for communicating quantitative information in an intelligent, effective and persuasive way. Topics covered include 1) writing and speaking about data; 2) data management in Excel in order to prepare data for charting; 3) understanding and ability to deploy core concepts in of design, layout, typography and color to maximize the impact of their data visualizations 4) determining which types of statistical measures are most effective for each type of data and message; 5) determining which types of design to use for communicating quantitative information; and 6) designing graphs and tables that are intelligent and compelling for communicating quantitative information.
- Class Notes:
- Class will be offered REMOTELY. Class will meet synchronously-online during Spring 2021 during the scheduled time. http://classinfo.umn.edu/?dorelien+PA5929+Spring2021
- Class Description:
- The class will have a practical approach, combining discussion and practical exercises. The course is designed to be like a walk-through, starting from collecting and organizing data and ending with advanced graph designs.The course in the spring will use Excel and Tableau. There will be additional modules available for more advance Excel users and those who want to go beyond the basics in Tableau. I will not teach R as part of the class but will make available the R modules and handouts for students that are interested in learning R.
- Learning Objectives:
- Learn to make better tables- see example below Learn to make better figures
- Grading:
- Please note that it is possible to audit the course or take the course S/N. I encourage students that are already taking a full load of classes to sign up for this class S/N, that way you can focus on learning the material and not on the letter grade.4 Problem Sets (each problem set is worth 15% of final grade). The problem sets will be due one week after being assigned and will need to be uploaded to Moodle before the start of class.
1 Final Report (30% of final grade) - Class Format:
- Meets twice a week for first half the semester. The majority of class time is spent doing in-class exercises.
- Textbooks:
- https://bookstores.umn.edu/course-lookup/54163/1213
- Past Syllabi:
- http://classinfo.umn.edu/syllabi/dorelien_PA5929_Spring2019.pdf (Spring 2019)
- Instructor Supplied Information Last Updated:
- 9 November 2020
Fall 2020 | PA 5929 Section 001: Data Visualization: Telling Stories with Numbers (20701)
- Instructor(s)
- Class Component:
- Laboratory
- Credits:
- 2 Credits
- Grading Basis:
- Student Option
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- Completely Online
- Class Attributes:
- Online Course
- Enrollment Requirements:
- Graduate Student
- Times and Locations:
- First Half of Term09/08/2020 - 10/26/2020Mon 05:30PM - 08:50PMOff CampusUMN REMOTE
- Enrollment Status:
- Open (42 of 45 seats filled)
- Also Offered:
- Course Catalog Description:
- Tools for communicating quantitative information in an intelligent, effective and persuasive way. Topics covered include 1) writing and speaking about data; 2) data management in Excel in order to prepare data for charting; 3) understanding and ability to deploy core concepts in of design, layout, typography and color to maximize the impact of their data visualizations 4) determining which types of statistical measures are most effective for each type of data and message; 5) determining which types of design to use for communicating quantitative information; and 6) designing graphs and tables that are intelligent and compelling for communicating quantitative information.
- Class Notes:
- PA 5929 will be offered REMOTELY. Class will meet synchronously-online during Fall 2020 (first half), Mondays, 5:30 - 8:50 p.m. PA 5929 will also be offered in Spring semester. http://classinfo.umn.edu/?maas0021+PA5929+Fall2020
- Class Description:
- This course will teach students how to organize and present data in the most effective way. Lectures will explore theories and elements of graphs and tables design, more specifically with how to create and organize tables and data. The central goal is to provide students with the tools for communicating information in an intelligent, effective and persuasive way.
- Who Should Take This Class?:
- Students interested in efficiently and effectively communicating data visually.
- Learning Objectives:
- Develop a firm understanding of the role of design, color, composition, type and statistical rigor in effectively communicating data visually.
- Grading:
- 15% class attendance and completion of in-class exercises
70% series of six assignments
15% final project - Exam Format:
- No exams
- Class Format:
- This class will combine lecture, in-class critique of data visualization approaches and discussion, and practical lab exercises and assignments. Classes will begin with a lecture to introduce topics to be explored and discussed. Hands-on work with the software will also be emphasized to allow students to complete the assignments and relate their skills to their own research interests.
- Workload:
- Weekly lectures including critique of data visualizations, in-class labs each week to help students gain familiarity with the tools and weekly assignments. Students will work with and become familiar with the core visualization functions in Microsoft Excel, Adobe Illustrator, Tableau and R.
- Textbooks:
- https://bookstores.umn.edu/course-lookup/20701/1209
- Past Syllabi:
- http://classinfo.umn.edu/syllabi/maas0021_PA5929_Fall2018.docx (Fall 2018)
http://classinfo.umn.edu/syllabi/maas0021_PA5929_Spring2018.pdf (Spring 2018) - Instructor Supplied Information Last Updated:
- 30 December 2019
Spring 2020 | PA 5929 Section 001: Data Visualization: Telling Stories with Numbers (57575)
- Instructor(s)
- Class Component:
- Laboratory
- Credits:
- 2 Credits
- Grading Basis:
- Student Option
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- In Person Term Based
- Times and Locations:
- First Half of Term01/21/2020 - 03/16/2020Tue, Thu 02:30PM - 03:45PMUMTC, West BankHubert H Humphrey Center 8502/08/2020Sat 10:00AM - 01:00PMUMTC, West BankHubert H Humphrey Center 85
- Enrollment Status:
- Open (31 of 32 seats filled)
- Also Offered:
- Course Catalog Description:
- Tools for communicating quantitative information in an intelligent, effective and persuasive way. Topics covered include 1) writing and speaking about data; 2) data management in Excel in order to prepare data for charting; 3) understanding and ability to deploy core concepts in of design, layout, typography and color to maximize the impact of their data visualizations 4) determining which types of statistical measures are most effective for each type of data and message; 5) determining which types of design to use for communicating quantitative information; and 6) designing graphs and tables that are intelligent and compelling for communicating quantitative information.
- Class Notes:
- http://classinfo.umn.edu/?dorelien+PA5929+Spring2020
- Class Description:
- The class will have a practical approach, combining discussion and practical exercises. The course is designed to be like a walk-through, starting from collecting and organizing data and ending with advanced graph designs.The course in the spring will only focus on Excel. There will be additional modules available for more advance Excel users. I will not teach R as part of the class but will make available the R modules and handouts for students that are interested in learning R. Based on demand I might also hold an extra voluntary R session.
- Learning Objectives:
- Learn to make better tables- see example below Learn to make better figures
- Grading:
- Please note that it is possible to audit the course or take the course S/N. I encourage students that are already taking a full load of classes to sign up for this class S/N, that way you can focus on learning the material and not on the letter grade.4 Problem Sets (each problem set is worth 15% of final grade). The problem sets will be due one week after being assigned and will need to be uploaded to Moodle before the start of class.
1 Final Report (30% of final grade) - Class Format:
- Meets twice a week for first half the semester. The majority of class time is spent doing in-class exercises.
- Textbooks:
- https://bookstores.umn.edu/course-lookup/57575/1203
- Past Syllabi:
- http://classinfo.umn.edu/syllabi/dorelien_PA5929_Spring2019.pdf (Spring 2019)
- Instructor Supplied Information Last Updated:
- 13 November 2018
Spring 2020 | PA 5929 Section 002: Data Visualization: Telling Stories with Numbers (57589)
- Instructor(s)
- Class Component:
- Laboratory
- Credits:
- 2 Credits
- Grading Basis:
- Student Option
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- In Person Term Based
- Times and Locations:
- Second Half of Term03/17/2020 - 05/04/2020Thu 05:30PM - 08:50PMUMTC, West BankHubert H Humphrey Center 85
- Enrollment Status:
- Open (32 of 33 seats filled)
- Also Offered:
- Course Catalog Description:
- Tools for communicating quantitative information in an intelligent, effective and persuasive way. Topics covered include 1) writing and speaking about data; 2) data management in Excel in order to prepare data for charting; 3) understanding and ability to deploy core concepts in of design, layout, typography and color to maximize the impact of their data visualizations 4) determining which types of statistical measures are most effective for each type of data and message; 5) determining which types of design to use for communicating quantitative information; and 6) designing graphs and tables that are intelligent and compelling for communicating quantitative information.
- Class Notes:
- http://classinfo.umn.edu/?maas0021+PA5929+Spring2020
- Class Description:
- This course will teach students how to organize and present data in the most effective way. Lectures will explore theories and elements of graphs and tables design, more specifically with how to create and organize tables and data. The central goal is to provide students with the tools for communicating information in an intelligent, effective and persuasive way.
- Who Should Take This Class?:
- Students interested in efficiently and effectively communicating data visually.
- Learning Objectives:
- Develop a firm understanding of the role of design, color, composition, type and statistical rigor in effectively communicating data visually.
- Grading:
- 15% class attendance and completion of in-class exercises
70% series of six assignments
15% final project - Exam Format:
- No exams
- Class Format:
- This class will combine lecture, in-class critique of data visualization approaches and discussion, and practical lab exercises and assignments. Classes will begin with a lecture to introduce topics to be explored and discussed. Hands-on work with the software will also be emphasized to allow students to complete the assignments and relate their skills to their own research interests.
- Workload:
- Weekly lectures including critique of data visualizations, in-class labs each week to help students gain familiarity with the tools and weekly assignments. Students will work with and become familiar with the core visualization functions in Microsoft Excel, Adobe Illustrator, Tableau and R.
- Textbooks:
- https://bookstores.umn.edu/course-lookup/57589/1203
- Past Syllabi:
- http://classinfo.umn.edu/syllabi/maas0021_PA5929_Fall2018.docx (Fall 2018)
http://classinfo.umn.edu/syllabi/maas0021_PA5929_Spring2018.pdf (Spring 2018) - Instructor Supplied Information Last Updated:
- 30 December 2019
Fall 2019 | PA 5929 Section 001: Data Visualization: Telling Stories with Numbers (23970)
- Instructor(s)
- Class Component:
- Laboratory
- Credits:
- 2 Credits
- Grading Basis:
- Student Option
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- In Person Term Based
- Times and Locations:
- First Half of Term09/03/2019 - 10/21/2019Mon 05:30PM - 08:50PMUMTC, West BankHubert H Humphrey Center 85
- Enrollment Status:
- Open (27 of 32 seats filled)
- Also Offered:
- Course Catalog Description:
- Tools for communicating quantitative information in an intelligent, effective and persuasive way. Topics covered include 1) writing and speaking about data; 2) data management in Excel in order to prepare data for charting; 3) understanding and ability to deploy core concepts in of design, layout, typography and color to maximize the impact of their data visualizations 4) determining which types of statistical measures are most effective for each type of data and message; 5) determining which types of design to use for communicating quantitative information; and 6) designing graphs and tables that are intelligent and compelling for communicating quantitative information.
- Class Notes:
- PA 5929 will also be offered in Spring semester. http://classinfo.umn.edu/?maas0021+PA5929+Fall2019
- Class Description:
- This course will teach students how to organize and present data in the most effective way. Lectures will explore theories and elements of graphs and tables design, more specifically with how to create and organize tables and data. The central goal is to provide students with the tools for communicating information in an intelligent, effective and persuasive way.
- Who Should Take This Class?:
- Students interested in efficiently and effectively communicating data visually.
- Learning Objectives:
- Develop a firm understanding of the role of design, color, composition, type and statistical rigor in effectively communicating data visually.
- Grading:
- 15% class attendance and completion of in-class exercises
70% series of six assignments
15% final project - Exam Format:
- No exams
- Class Format:
- This class will combine lecture, discussion, and practical exercises. Classes will begin with short lecture to introduce topics to be explored and discussed. Hands-on work with the software will also be emphasized to allow students to complete the assignments and relate their skills to their own research interests.
- Workload:
- Weekly lectures including critique of data visualizations, in-class labs each week to help students gain familiarity with the tools and weekly assignments.
- Textbooks:
- https://bookstores.umn.edu/course-lookup/23970/1199
- Past Syllabi:
- http://classinfo.umn.edu/syllabi/maas0021_PA5929_Fall2018.docx (Fall 2018)
http://classinfo.umn.edu/syllabi/maas0021_PA5929_Spring2018.pdf (Spring 2018) - Instructor Supplied Information Last Updated:
- 10 November 2017
Spring 2019 | PA 5929 Section 001: Data Visualization: Telling Stories with Numbers (58245)
- Instructor(s)
- Class Component:
- Laboratory
- Credits:
- 1.5 Credits
- Grading Basis:
- Student Option
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- In Person Term Based
- Times and Locations:
- First Half of Term01/22/2019 - 03/11/2019Tue, Thu 02:30PM - 03:45PMUMTC, West BankHubert H Humphrey Center 85
- Enrollment Status:
- Closed (32 of 32 seats filled)
- Also Offered:
- Course Catalog Description:
- Tools for communicating quantitative information in an intelligent, effective and persuasive way. Topics covered include 1) determining which types of statistical measures are most effective for each type of data and message; 2) determining which types of design to use for communicating quantitative information; and 3) designing graphs and tables that are intelligent and compelling for communicating quantitative information.
- Class Notes:
- http://classinfo.umn.edu/?dorelien+PA5929+Spring2019
- Class Description:
- The class will have a practical approach, combining discussion and practical exercises. The course is designed to be like a walk-through, starting from collecting and organizing data and ending with advanced graph designs.The course in the spring will only focus on Excel. There will be additional modules available for more advance Excel users. I will not teach R as part of the class but will make available the R modules and handouts for students that are interested in learning R. Based on demand I might also hold an extra voluntary R session.
- Learning Objectives:
- Learn to make better tables- see example below Learn to make better figures
- Grading:
- Please note that it is possible to audit the course or take the course S/N. I encourage students that are already taking a full load of classes to sign up for this class S/N, that way you can focus on learning the material and not on the letter grade.4 Problem Sets (each problem set is worth 15% of final grade). The problem sets will be due one week after being assigned and will need to be uploaded to Moodle before the start of class.
1 Final Report (30% of final grade) - Class Format:
- Meets twice a week for first half the semester. The majority of class time is spent doing in-class exercises.
- Textbooks:
- https://bookstores.umn.edu/course-lookup/58245/1193
- Syllabus:
- http://classinfo.umn.edu/syllabi/dorelien_PA5929_Spring2019.pdf
- Instructor Supplied Information Last Updated:
- 13 November 2018
Spring 2019 | PA 5929 Section 002: Data Visualization: Telling Stories with Numbers (58277)
- Instructor(s)
- Class Component:
- Laboratory
- Credits:
- 1.5 Credits
- Grading Basis:
- Student Option
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- In Person Term Based
- Times and Locations:
- Second Half of Term03/12/2019 - 05/06/2019Tue, Thu 04:00PM - 05:15PMUMTC, West BankHubert H Humphrey Center 85
- Enrollment Status:
- Open (31 of 32 seats filled)
- Also Offered:
- Course Catalog Description:
- Tools for communicating quantitative information in an intelligent, effective and persuasive way. Topics covered include 1) determining which types of statistical measures are most effective for each type of data and message; 2) determining which types of design to use for communicating quantitative information; and 3) designing graphs and tables that are intelligent and compelling for communicating quantitative information.
- Class Notes:
- http://classinfo.umn.edu/?dorelien+PA5929+Spring2019
- Class Description:
- The class will have a practical approach, combining discussion and practical exercises. The course is designed to be like a walk-through, starting from collecting and organizing data and ending with advanced graph designs.The course in the spring will only focus on Excel. There will be additional modules available for more advance Excel users. I will not teach R as part of the class but will make available the R modules and handouts for students that are interested in learning R. Based on demand I might also hold an extra voluntary R session.
- Learning Objectives:
- Learn to make better tables- see example below Learn to make better figures
- Grading:
- Please note that it is possible to audit the course or take the course S/N. I encourage students that are already taking a full load of classes to sign up for this class S/N, that way you can focus on learning the material and not on the letter grade.4 Problem Sets (each problem set is worth 15% of final grade). The problem sets will be due one week after being assigned and will need to be uploaded to Moodle before the start of class.
1 Final Report (30% of final grade) - Class Format:
- Meets twice a week for first half the semester. The majority of class time is spent doing in-class exercises.
- Textbooks:
- https://bookstores.umn.edu/course-lookup/58277/1193
- Syllabus:
- http://classinfo.umn.edu/syllabi/dorelien_PA5929_Spring2019.pdf
- Instructor Supplied Information Last Updated:
- 13 November 2018
Fall 2018 | PA 5929 Section 001: Data Visualization: Telling Stories with Numbers (24357)
- Instructor(s)
- Class Component:
- Laboratory
- Credits:
- 1.5 Credits
- Grading Basis:
- Student Option
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- In Person Term Based
- Times and Locations:
- First Half of Term09/04/2018 - 10/22/2018Mon 06:00PM - 08:45PMUMTC, West BankHubert H Humphrey Center 85
- Enrollment Status:
- Closed (27 of 25 seats filled)
- Also Offered:
- Course Catalog Description:
- Tools for communicating quantitative information in an intelligent, effective and persuasive way. Topics covered include 1) determining which types of statistical measures are most effective for each type of data and message; 2) determining which types of design to use for communicating quantitative information; and 3) designing graphs and tables that are intelligent and compelling for communicating quantitative information.
- Class Notes:
- PA 5929 will also be offered in Spring semester. http://classinfo.umn.edu/?maas0021+PA5929+Fall2018
- Class Description:
- This course will teach students how to organize and present data in the most effective way. Lectures will explore theories and elements of graphs and tables design, more specifically with how to create and organize tables and data. The central goal is to provide students with the tools for communicating information in an intelligent, effective and persuasive way.
- Who Should Take This Class?:
- Students interested in efficiently and effectively communicating data visually.
- Learning Objectives:
- Develop a firm understanding of the role of design, color, composition, type and statistical rigor in effectively communicating data visually.
- Grading:
- 15% class attendance and completion of in-class exercises
70% series of six assignments
15% final project - Exam Format:
- No exams
- Class Format:
- This class will combine lecture, discussion, and practical exercises. Classes will begin with short lecture to introduce topics to be explored and discussed. Hands-on work with the software will also be emphasized to allow students to complete the assignments and relate their skills to their own research interests.
- Workload:
- Weekly lectures including critique of data visualizations, in-class labs each week to help students gain familiarity with the tools and weekly assignments.
- Textbooks:
- https://bookstores.umn.edu/course-lookup/24357/1189
- Syllabus:
- http://classinfo.umn.edu/syllabi/maas0021_PA5929_Fall2018.docx
- Past Syllabi:
- http://classinfo.umn.edu/syllabi/maas0021_PA5929_Spring2018.pdf (Spring 2018)
- Instructor Supplied Information Last Updated:
- 10 November 2017
Spring 2018 | PA 5929 Section 001: Data Visualization: Telling Stories with Numbers (54940)
- Instructor(s)
- Class Component:
- Laboratory
- Credits:
- 1.5 Credits
- Grading Basis:
- Student Option
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- In Person Term Based
- Times and Locations:
- Second Half of Term03/19/2018 - 05/04/2018Mon 06:00PM - 08:45PMUMTC, West BankHubert H Humphrey Center 85
- Enrollment Status:
- Open (32 of 34 seats filled)
- Also Offered:
- Course Catalog Description:
- Tools for communicating quantitative information in an intelligent, effective and persuasive way. Topics covered include 1) determining which types of statistical measures are most effective for each type of data and message; 2) determining which types of design to use for communicating quantitative information; and 3) designing graphs and tables that are intelligent and compelling for communicating quantitative information.
- Class Notes:
- http://classinfo.umn.edu/?maas0021+PA5929Spring2018
- Class Description:
- This course will teach students how to organize and present data in the most effective way. Lectures will explore theories and elements of graphs and tables design, more specifically with how to create and organize tables and data. The central goal is to provide students with the tools for communicating information in an intelligent, effective and persuasive way.
- Who Should Take This Class?:
- Students interested in efficiently and effectively communicating data visually.
- Learning Objectives:
- Develop a firm understanding of the role of design, color, composition, type and statistical rigor in effectively communicating data visually.
- Grading:
- 15% class attendance and completion of in-class exercises
70% series of six assignments
15% final project - Exam Format:
- No exams
- Class Format:
- This class will combine lecture, discussion, and practical exercises. Classes will begin with short lecture to introduce topics to be explored and discussed. Hands-on work with the software will also be emphasized to allow students to complete the assignments and relate their skills to their own research interests.
- Workload:
- Weekly lectures including critique of data visualizations, in-class labs each week to help students gain familiarity with the tools and weekly assignments.
- Textbooks:
- https://bookstores.umn.edu/course-lookup/54940/1183
- Syllabus:
- http://classinfo.umn.edu/syllabi/maas0021_PA5929_Spring2018.pdf
- Past Syllabi:
- http://classinfo.umn.edu/syllabi/maas0021_PA5929_Fall2018.docx (Fall 2018)
- Instructor Supplied Information Last Updated:
- 10 November 2017
Spring 2018 | PA 5929 Section 002: Data Visualization: Telling Stories with Numbers (67035)
- Instructor(s)
- Class Component:
- Laboratory
- Credits:
- 1.5 Credits
- Grading Basis:
- Student Option
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- In Person Term Based
- Times and Locations:
- First Half of Term01/16/2018 - 03/05/2018Tue, Thu 02:30PM - 03:45PMUMTC, West BankHubert H Humphrey Center 85
- Enrollment Status:
- Closed (31 of 25 seats filled)
- Also Offered:
- Course Catalog Description:
- Tools for communicating quantitative information in an intelligent, effective and persuasive way. Topics covered include 1) determining which types of statistical measures are most effective for each type of data and message; 2) determining which types of design to use for communicating quantitative information; and 3) designing graphs and tables that are intelligent and compelling for communicating quantitative information.
- Class Notes:
- http://classinfo.umn.edu/?dorelien+PA5929Spring2018
- Class Description:
- Please note that it is possible to audit the course or take the course S/N.The course in the spring will only focus on Excel (and possibly Tableau) and will be geared towards students who really haven't used Excel much. The spring course will meet twice a week for the first half of the semester. Both the fall and spring courses will cover the same key concepts, it's just that in the fall course you will learn how to make the visualizations in both Excel and R.If there is enough student interest, the last two weeks of the course will be an introduction to Tableau (https://public.tableau.com/s/).
- Grading:
- Please note that it is possible to audit the course or take the course S/N. I encourage students that are already taking a full load of classes to sign up for this class S/N, that way you can focus on learning the material and not on the letter grade.6 Problem Sets (each problem set is worth 11% of final grade). The problem sets will be due one week after being assigned and will need to be uploaded to Moodle before the start of class.
1 Final Report (34% of final grade) - Class Format:
- Meets twice a week for first half the semester. The majority of class time is spent doing in-class exercises.
- Textbooks:
- https://bookstores.umn.edu/course-lookup/67035/1183
- Past Syllabi:
- http://classinfo.umn.edu/syllabi/dorelien_PA5929_Spring2019.pdf (Spring 2019)
- Instructor Supplied Information Last Updated:
- 15 November 2017
Fall 2017 | PA 5929 Section 001: Data Visualization: Telling Stories with Numbers (21352)
- Instructor(s)
- Class Component:
- Laboratory
- Credits:
- 1.5 Credits
- Grading Basis:
- Student Option
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- In Person Term Based
- Times and Locations:
- First Half of Term09/05/2017 - 10/23/2017Mon 06:00PM - 08:45PMUMTC, West BankHubert H Humphrey Center 85
- Also Offered:
- Course Catalog Description:
- Tools for communicating quantitative information in an intelligent, effective and persuasive way. Topics covered include 1) determining which types of statistical measures are most effective for each type of data and message; 2) determining which types of design to use for communicating quantitative information; and 3) designing graphs and tables that are intelligent and compelling for communicating quantitative information.
- Class Notes:
- PA 5929 will also be offered in Spring semester. http://classinfo.umn.edu/?maas0021+PA5929+Fall2017
- Class Description:
- This course will teach students how to organize and present data in the most effective way. Lectures will explore theories and elements of graphs and tables design, more specifically with how to create and organize tables and data. The central goal is to provide students with the tools for communicating information in an intelligent, effective and persuasive way.
- Grading:
- 15% class attendance and in-class exercises
70% series of five assignments
15% final report and presentation - Exam Format:
- no exams
- Class Format:
- This class will combine lecture, discussion, and practical exercises. Classes will begin with short lecture to introduce topics to be explored and discussed. Hands-on work with the software will also be emphasized to allow students to complete the assignments and relate their skills to their own research interests.
- Textbooks:
- https://bookstores.umn.edu/course-lookup/21352/1179
- Past Syllabi:
- http://classinfo.umn.edu/syllabi/maas0021_PA5929_Fall2018.docx (Fall 2018)
http://classinfo.umn.edu/syllabi/maas0021_PA5929_Spring2018.pdf (Spring 2018) - Instructor Supplied Information Last Updated:
- 10 August 2016
Spring 2017 | PA 5929 Section 001: Data Visualization: Telling Stories with Numbers (67844)
- Instructor(s)
- Class Component:
- Laboratory
- Credits:
- 1.5 Credits
- Grading Basis:
- Student Option
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- In Person Term Based
- Times and Locations:
- First Half of Term01/17/2017 - 03/06/2017Mon 06:00PM - 08:45PMUMTC, West BankHubert H Humphrey Center 85
- Also Offered:
- Course Catalog Description:
- Tools for communicating quantitative information in an intelligent, effective and persuasive way. Topics covered include 1) determining which types of statistical measures are most effective for each type of data and message; 2) determining which types of design to use for communicating quantitative information; and 3) designing graphs and tables that are intelligent and compelling for communicating quantitative information.
- Class Notes:
- http://classinfo.umn.edu/?maas0021+PA5929Spring2017
- Class Description:
- This course will teach students how to organize and present data in the most effective way. Lectures will explore theories and elements of graphs and tables design, more specifically with how to create and organize tables and data. The central goal is to provide students with the tools for communicating information in an intelligent, effective and persuasive way.
- Grading:
- 15% class attendance and in-class exercises
70% series of five assignments
15% final report and presentation - Exam Format:
- no exams
- Class Format:
- This class will combine lecture, discussion, and practical exercises. Classes will begin with short lecture to introduce topics to be explored and discussed. Hands-on work with the software will also be emphasized to allow students to complete the assignments and relate their skills to their own research interests.
- Textbooks:
- https://bookstores.umn.edu/course-lookup/67844/1173
- Past Syllabi:
- http://classinfo.umn.edu/syllabi/maas0021_PA5929_Fall2018.docx (Fall 2018)
http://classinfo.umn.edu/syllabi/maas0021_PA5929_Spring2018.pdf (Spring 2018) - Instructor Supplied Information Last Updated:
- 10 August 2016
Fall 2016 | PA 5929 Section 001: Data Visualization: Telling Stories with Numbers (35524)
- Instructor(s)
- Class Component:
- Laboratory
- Credits:
- 1.5 Credits
- Grading Basis:
- Student Option
- Instructor Consent:
- No Special Consent Required
- Instruction Mode:
- In Person Term Based
- Times and Locations:
- First Half of Term09/06/2016 - 10/24/2016Mon 06:00PM - 08:45PMUMTC, West BankHubert H Humphrey Center 85
- Also Offered:
- Course Catalog Description:
- Tools for communicating quantitative information in an intelligent, effective and persuasive way. Topics covered include 1) determining which types of statistical measures are most effective for each type of data and message; 2) determining which types of design to use for communicating quantitative information; and 3) designing graphs and tables that are intelligent and compelling for communicating quantitative information.
- Class Notes:
- http://classinfo.umn.edu/?maas0021+PA5929+Fall2016
- Class Description:
- This course will teach students how to organize and present data in the most effective way. Lectures will explore theories and elements of graphs and tables design, more specifically with how to create and organize tables and data. The central goal is to provide students with the tools for communicating information in an intelligent, effective and persuasive way.
- Grading:
- 15% class attendance and in-class exercises
70% series of five assignments
15% final report and presentation - Exam Format:
- no exams
- Class Format:
- This class will combine lecture, discussion, and practical exercises. Classes will begin with short lecture to introduce topics to be explored and discussed. Hands-on work with the software will also be emphasized to allow students to complete the assignments and relate their skills to their own research interests.
- Textbooks:
- https://bookstores.umn.edu/course-lookup/35524/1169
- Past Syllabi:
- http://classinfo.umn.edu/syllabi/maas0021_PA5929_Fall2018.docx (Fall 2018)
http://classinfo.umn.edu/syllabi/maas0021_PA5929_Spring2018.pdf (Spring 2018) - Instructor Supplied Information Last Updated:
- 10 August 2016
ClassInfo Links - Public Affairs Classes
- To link directly to this ClassInfo page from your website or to save it as a bookmark, use:
- http://classinfo.umn.edu/?subject=PA&catalog_nbr=5929
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- http://classinfo.umn.edu/?subject=PA&catalog_nbr=5929&xml=1
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- http://classinfo.umn.edu/?subject=PA&catalog_nbr=5929&csv=1
ClassInfo created and maintained by the Humphrey School of Public Affairs.
If you have questions about specific courses, we strongly encourage you to contact the department where the course resides.