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Defining, Describing, and Visualizing Data
Wendy Martin
Wendy Martin
As leaders in your chosen field, you need to not only know how to ask the right questions but also answer them using data-based methods. Through this class, you will be able to get to the bottom of what you really want to know, describe the associated data related to that question, and visualize the information from that data to understand and explain the results.
Read more
As leaders in your chosen field, you need to not only know how to ask the right questions but also answer them using data-based methods. Through this class, you will be able to get to the bottom of what you really want to know, describe the associated data related to that question, and visualize the information from that data to understand and explain the results.
Read more
As leaders in your chosen field, you need to not only know how to ask the right questions but also answer them using data-based methods. Through this class, you will be able to get to the bottom of what you really want to know, describe the associated data related to that question, and visualize the information from that data to understand and explain the results.
This course can be taken for academic credit as part of CU Boulder’s Master of Engineering in Engineering Management (ME-EM) degree offered on the Coursera platform. The ME-EM is designed to help engineers, scientists, and technical professionals move into leadership and management roles in the engineering and technical sectors. With performance-based admissions and no application process, the ME-EM is ideal for individuals with a broad range of undergraduate education and/or professional experience. Learn more about the ME-EM program at https://www.coursera.org/degrees/me-engineering-management-boulder.
Register for this course and see more details by visiting:
OpenCourser.com/course/zzw486/defining
What's inside
Syllabus
Data and Measurement
Upon completion of this module, students will be able to classify types of data using measurement scales.
Working with Data in RStudio and ROIStat
Read more
Syllabus
Data and Measurement
Upon completion of this module, students will be able to classify types of data using measurement scales.
Working with Data in RStudio and ROIStat
Read more
Upon completion of this module, students will be able to work with datasets in RStudio and ROIStat.
Describing and Visualizing Data
Upon completion of this module, students will be able to use RStudio and ROIStat to calculate descriptive statistics to describe location, spread, and shape of data and create visual representations of data.
Determining Probabilities
Upon completion of this module, students will be able to apply the rules and conditions of probability to make decisions and solve problems.
Making Decisions with Discrete and Continuous Probability Distributions
Upon completion of this module, students will be able to apply both discrete and continuous probability distributions to make decisions and solve problems using RStudio and ROIStat.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Covers foundational data science topics, from data acquisition to analysis, providing a well-rounded base
Utilizes industry-standard software and tools, such as RStudio and ROIStat, equipping learners with practical skills
Builds a strong foundation in probability and statistics, essential for data analysis and decision-making
Led by instructors with extensive experience in data science, ensuring up-to-date knowledge and industry insights
May require prior exposure to data science or proficiency in statistical software, suitable for learners with some background knowledge
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Activities
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Defining, Describing, and Visualizing Data.
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Career center
Learners who complete Defining, Describing, and Visualizing Data will develop knowledge and skills
that may be useful to these careers:
Data Analyst
Data Analyst
Data Analysts are responsible for collecting, cleaning, and analyzing data to help businesses make informed decisions. This course provides a strong foundation in data analysis techniques and tools, such as RStudio and ROIStat, which are essential for success in this role. The course also covers topics such as probability and statistics, which are important for understanding and interpreting data.
Statistician
Statistician
Statisticians collect, analyze, and interpret data to help businesses and organizations make informed decisions. This course provides a strong foundation in statistical methods and techniques, such as RStudio and ROIStat, which are essential for success in this role. The course also covers topics such as probability and statistics, which are important for understanding and interpreting data.
Data Scientist
Data Scientist
Data Scientists use data to solve complex business problems. This course provides a strong foundation in data science techniques and tools, such as RStudio and ROIStat, which are essential for success in this role. The course also covers topics such as probability and statistics, which are important for understanding and interpreting data.
Market Researcher
Market Researcher
Market Researchers collect and analyze data to help businesses understand their customers and make informed decisions. This course provides a strong foundation in data analysis techniques and tools, such as RStudio and ROIStat, which are essential for success in this role. The course also covers topics such as probability and statistics, which are important for understanding and interpreting data.
Business Analyst
Business Analyst
Business Analysts use data to help businesses improve their performance. This course provides a strong foundation in data analysis techniques and tools, such as RStudio and ROIStat, which are essential for success in this role. The course also covers topics such as probability and statistics, which are important for understanding and interpreting data.
Risk Analyst
Risk Analyst
Risk Analysts use data to help businesses identify and mitigate risks. This course provides a strong foundation in data analysis techniques and tools, such as RStudio and ROIStat, which are essential for success in this role. The course also covers topics such as probability and statistics, which are important for understanding and interpreting data.
Financial Analyst
Financial Analyst
Financial Analysts use data to help businesses make informed decisions about investments and financial planning. This course provides a strong foundation in data analysis techniques and tools, such as RStudio and ROIStat, which are essential for success in this role. The course also covers topics such as probability and statistics, which are important for understanding and interpreting data.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use data to help businesses improve their operations and make informed decisions. This course provides a strong foundation in data analysis techniques and tools, such as RStudio and ROIStat, which are essential for success in this role. The course also covers topics such as probability and statistics, which are important for understanding and interpreting data.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use data to help businesses make informed decisions about investments and financial planning. This course provides a strong foundation in data analysis techniques and tools, such as RStudio and ROIStat, which are essential for success in this role. The course also covers topics such as probability and statistics, which are important for understanding and interpreting data.
Database Administrator
Database Administrator
Database Administrators manage and maintain databases. This course provides a strong foundation in database administration techniques and tools, such as RStudio and ROIStat, which are essential for success in this role. The course also covers topics such as probability and statistics, which are important for understanding and interpreting data.
Software Engineer
Software Engineer
Software Engineers design, develop, and maintain software applications. This course provides a strong foundation in software engineering principles and techniques, such as RStudio and ROIStat, which are essential for success in this role. The course also covers topics such as probability and statistics, which are important for understanding and interpreting data.
Project Manager
Project Manager
Project Managers plan, execute, and control projects. This course provides a strong foundation in project management principles and techniques, such as RStudio and ROIStat, which are essential for success in this role. The course also covers topics such as probability and statistics, which are important for understanding and interpreting data.
Product Manager
Product Manager
Product Managers are responsible for the development and management of products. This course provides a strong foundation in product management principles and techniques, such as RStudio and ROIStat, which are essential for success in this role. The course also covers topics such as probability and statistics, which are important for understanding and interpreting data.
Consultant
Consultant
Consultants provide advice and guidance to businesses and organizations. This course provides a strong foundation in consulting principles and techniques, such as RStudio and ROIStat, which are essential for success in this role. The course also covers topics such as probability and statistics, which are important for understanding and interpreting data.
Data Engineer
Data Engineer
Data Engineers build and maintain the infrastructure that stores and processes data. This course provides a strong foundation in data engineering techniques and tools, such as RStudio and ROIStat, which are essential for success in this role. The course also covers topics such as probability and statistics, which are important for understanding and interpreting data.
For more career information including salaries, visit:
OpenCourser.com/course/zzw486/defining
Reading list
We've selected 13 books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Defining, Describing, and Visualizing Data.
This influential book introduces Bayesian statistical methods, which are becoming increasingly important in data analysis and decision-making.
This renowned textbook provides a comprehensive overview of statistical learning methods, including supervised and unsupervised learning algorithms.
Save
Serves as a comprehensive guide to data visualization principles and techniques, offering practical advice on creating clear and effective visualizations.
Introduces Bayesian statistical methods using R and Stan, providing practical experience with Bayesian modeling and inference.
This practical guide offers step-by-step instructions and hands-on examples that demonstrate how to use R and RStudio for data visualization. It serves as a valuable complement to the course's focus on visualization techniques.
This classic textbook offers a comprehensive introduction to probability models, providing a solid foundation for understanding the probabilistic aspects of data analysis.
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This comprehensive resource covers the fundamental concepts and algorithms of deep learning, providing valuable insights into the latest advancements in data-driven decision-making.
This classic textbook introduces the principles of reinforcement learning, which is becoming increasingly important in artificial intelligence and data-driven decision-making.
Save
Provides a comprehensive overview of causal inference methods, which are essential for making reliable decisions based on observational data.
This textbook provides a solid foundation in discrete mathematics, covering topics such as set theory, logic, and probability, which are essential for understanding the underlying principles of data analysis.
This textbook provides an foundational overview of statistics and its foundational concepts. It could serve as additional reading for those in the course who may need to review or who want more context and background on statistical methods.
Explores the statistical methods and models used in financial engineering, providing valuable insights into the application of data-based decision-making in the financial sector.
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Provides a high level overview of data science and offers valuable insights into the ethical implications and limitations of data-based decision-making.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/zzw486/defining
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Level
Introductory
Via
Coursera
Institution
University of Colorado Boulder
Instructor
Wendy Martin
Language
English
This course belongs to a
collection
called
The Data Driven Manager. It's comprised of three courses:
- Defining, Describing, and Visualizing Data (viewing)
- Data Driven Decision Making
- Data Acquisition, Risk, and Estimation
Good to know
Covers foundational data science topics, from data acquisition to analysis, providing a well-rounded base
Utilizes industry-standard software and tools, such as RStudio and ROIStat, equipping learners with practical skills
Builds a strong foundation in probability and statistics, essential for data analysis and decision-making
Led by instructors with extensive experience in data science, ensuring up-to-date knowledge and industry insights
May require prior exposure to data science or proficiency in statistical software, suitable for learners with some background knowledge
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