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Wendy Martin
Once we have generated data, we need to answer the research question by performing an appropriate statistical analysis. Engineers and business professionals need to know which test or tests to use. Through this class, you will be able to perform one sample tests for comparison to historical data. You will also be able to determine statistically significant relationships between two variables. You will be able to perform two sample tests for both independent and dependent data. Finally, you will analyze data with more than two groups using the Analysis of Variance.
Read more
Once we have generated data, we need to answer the research question by performing an appropriate statistical analysis. Engineers and business professionals need to know which test or tests to use. Through this class, you will be able to perform one sample tests for comparison to historical data. You will also be able to determine statistically significant relationships between two variables. You will be able to perform two sample tests for both independent and dependent data. Finally, you will analyze data with more than two groups using the Analysis of Variance.
Read more
Once we have generated data, we need to answer the research question by performing an appropriate statistical analysis. Engineers and business professionals need to know which test or tests to use. Through this class, you will be able to perform one sample tests for comparison to historical data. You will also be able to determine statistically significant relationships between two variables. You will be able to perform two sample tests for both independent and dependent data. Finally, you will analyze data with more than two groups using the Analysis of Variance.
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/0mghlg/data
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What's inside
Syllabus
One Sample Tests
Upon completion of this module, students will be able compare generated data to historical data for both continuous and discrete data using RStudio and ROIStat.
Read more
Syllabus
One Sample Tests
Upon completion of this module, students will be able compare generated data to historical data for both continuous and discrete data using RStudio and ROIStat.
Read more
Correlation and Association
Upon completion of this module, students will be able to determine relationships between two variables for both continuous and discrete data using RStudio and ROIStat.
Two Sample Tests for Independent Data
Upon completion of this module, students will be able to compare two independent samples for both continuous and discrete data using RStudio and ROIStat.
Two Sample Tests for Dependent Data
Upon completion of this module, students will be able to compare two dependent samples for both continuous and discrete data using RStudio and ROIStat.
The One Way Analysis of Variance
Upon completion of this module, students will be able to analyze continuous data with more than 2 groups using RStudio and ROIStat.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Taught by Wendy Martin, who is recognized for their work in engineering management
Meant for engineers and business professionals who need help choosing appropriate statistical tests
Introduces one sample tests for comparison to historical data
Presents two sample tests for both independent and dependent data
Features the Analysis of Variance for analyzing data with more than two groups
Students will need access to RStudio and ROIStat software
Save this course
Save Data Driven Decision Making to your list so you can find it easily later:
Save
Save
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Data Driven Decision Making with these
activities:
Review biostatistics foundations
Show steps
Refreshing your knowledge of biostatistics will provide a strong foundation for understanding the statistical analysis methods covered in this course.
Browse courses on
Biostatistics
Show steps
-
Review notes and materials from previous biostatistics courses.
-
Read introductory chapters of a biostatistics textbook.
-
Complete practice problems to test your understanding.
Review Statistical Probability Concepts
Show steps
Strengthen your foundation in statistical probability to enhance your understanding of the course material.
Browse courses on
Probability Theory
Show steps
-
Revisit textbooks or online resources on probability theory.
-
Solve practice problems to test your comprehension.
-
Attend optional review sessions or consult with a tutor.
Form a Study Group for Course Discussion and Support
Show steps
Enhance your learning experience by collaborating with peers, discussing course material, and providing mutual support.
Show steps
-
Connect with classmates online or in person.
-
Schedule regular study sessions.
-
Review course material together.
-
Discuss concepts and share insights.
Nine other activities
Expand to see all activities and additional details
Show all 12 activities
Explore RStudio and ROIStat
Show steps
Gaining familiarity with RStudio and ROIStat will help you efficiently complete the statistical analysis assignments in this course.
Browse courses on
RStudio
Show steps
-
Follow beginner tutorials on RStudio and ROIStat.
-
Practice loading and manipulating data in RStudio.
Create a Personalized Course Notebook
Show steps
Organize course materials and enhance comprehension by creating a customized notebook that aligns with your learning style.
Browse courses on
Note-Taking
Show steps
-
Gather course notes, slides, and assignments.
-
Review and synthesize the collected materials.
-
Create a structured notebook using your preferred format (digital or physical).
-
Incorporate summaries, examples, and any additional resources.
Practice Data Analysis with RStudio and ROIStat
Show steps
Enhance your data analysis skills through hands-on exercises, reinforcing concepts covered in the modules.
Browse courses on
Statistical Analysis
Show steps
-
Install RStudio and ROIStat software.
-
Import and clean a dataset using RStudio.
-
Perform one-sample tests using ROIStat.
-
Analyze relationships between variables using ROIStat.
Complete practice problems on statistical tests
Show steps
Regular practice with statistical tests will improve your problem-solving skills and enhance your understanding of the concepts.
Show steps
-
Solve practice problems from textbooks or online resources.
-
Participate in online forums to discuss solutions with peers.
Write a Blog Post Summarizing Key Statistical Concepts
Show steps
Improve your communication and comprehension skills by explaining statistical concepts in a clear and engaging manner.
Browse courses on
Content Creation
Show steps
-
Identify a statistical concept covered in the course.
-
Research and gather supporting information.
-
Write a blog post that explains the concept in accessible language.
-
Proofread and publish your post.
Create a cheat sheet on statistical formulas
Show steps
Creating a cheat sheet will help you memorize key statistical formulas and improve your understanding of the underlying concepts.
Show steps
-
Review statistical formulas from textbooks and notes.
-
Organize the formulas into a concise and easy-to-understand cheat sheet.
Contribute to the RStudio or ROIStat Open-Source Community
Show steps
Enhance your technical skills and contribute to the statistical analysis community by participating in open-source projects.
Browse courses on
RStudio
Show steps
-
Explore RStudio or ROIStat GitHub repositories.
-
Identify an issue or feature to work on.
-
Create or review pull requests.
Attend industry webinars and conferences
Show steps
Networking with professionals in the field will provide insights into real-world applications of statistical analysis and potential career opportunities.
Browse courses on
Career Development
Show steps
-
Search for upcoming webinars and conferences related to data analysis.
-
Register and attend the events.
-
Connect with speakers and attendees to learn about their experiences.
Develop a Statistical Model for a Real-World Problem
Show steps
Apply your statistical knowledge to a practical problem, deepening your understanding and developing your problem-solving abilities.
Browse courses on
Statistical Modeling
Show steps
-
Identify a real-world dataset related to your field of interest.
-
Clean and prepare the dataset for analysis.
-
Develop and evaluate statistical models to uncover insights.
-
Present your findings and make recommendations.
Review biostatistics foundations
Show steps
Refreshing your knowledge of biostatistics will provide a strong foundation for understanding the statistical analysis methods covered in this course.
Browse courses on
Biostatistics
Show steps
Show steps
Show steps
- Review notes and materials from previous biostatistics courses.
- Read introductory chapters of a biostatistics textbook.
- Complete practice problems to test your understanding.
Review Statistical Probability Concepts
Show steps
Strengthen your foundation in statistical probability to enhance your understanding of the course material.
Browse courses on
Probability Theory
Show steps
Show steps
Show steps
- Revisit textbooks or online resources on probability theory.
- Solve practice problems to test your comprehension.
- Attend optional review sessions or consult with a tutor.
Form a Study Group for Course Discussion and Support
Show steps
Enhance your learning experience by collaborating with peers, discussing course material, and providing mutual support.
Show steps
Show steps
Show steps
- Connect with classmates online or in person.
- Schedule regular study sessions.
- Review course material together.
- Discuss concepts and share insights.
Nine other activities
Expand to see all activities and additional details
Show all 12 activities
Explore RStudio and ROIStat
Show steps
Gaining familiarity with RStudio and ROIStat will help you efficiently complete the statistical analysis assignments in this course.
Browse courses on
RStudio
Show steps
Show steps
Show steps
- Follow beginner tutorials on RStudio and ROIStat.
- Practice loading and manipulating data in RStudio.
Create a Personalized Course Notebook
Show steps
Organize course materials and enhance comprehension by creating a customized notebook that aligns with your learning style.
Browse courses on
Note-Taking
Show steps
Show steps
Show steps
- Gather course notes, slides, and assignments.
- Review and synthesize the collected materials.
- Create a structured notebook using your preferred format (digital or physical).
- Incorporate summaries, examples, and any additional resources.
Practice Data Analysis with RStudio and ROIStat
Show steps
Enhance your data analysis skills through hands-on exercises, reinforcing concepts covered in the modules.
Browse courses on
Statistical Analysis
Show steps
Show steps
Show steps
- Install RStudio and ROIStat software.
- Import and clean a dataset using RStudio.
- Perform one-sample tests using ROIStat.
- Analyze relationships between variables using ROIStat.
Complete practice problems on statistical tests
Show steps
Regular practice with statistical tests will improve your problem-solving skills and enhance your understanding of the concepts.
Show steps
Show steps
Show steps
- Solve practice problems from textbooks or online resources.
- Participate in online forums to discuss solutions with peers.
Write a Blog Post Summarizing Key Statistical Concepts
Show steps
Improve your communication and comprehension skills by explaining statistical concepts in a clear and engaging manner.
Browse courses on
Content Creation
Show steps
Show steps
Show steps
- Identify a statistical concept covered in the course.
- Research and gather supporting information.
- Write a blog post that explains the concept in accessible language.
- Proofread and publish your post.
Create a cheat sheet on statistical formulas
Show steps
Creating a cheat sheet will help you memorize key statistical formulas and improve your understanding of the underlying concepts.
Show steps
Show steps
Show steps
- Review statistical formulas from textbooks and notes.
- Organize the formulas into a concise and easy-to-understand cheat sheet.
Contribute to the RStudio or ROIStat Open-Source Community
Show steps
Enhance your technical skills and contribute to the statistical analysis community by participating in open-source projects.
Browse courses on
RStudio
Show steps
Show steps
Show steps
- Explore RStudio or ROIStat GitHub repositories.
- Identify an issue or feature to work on.
- Create or review pull requests.
Attend industry webinars and conferences
Show steps
Networking with professionals in the field will provide insights into real-world applications of statistical analysis and potential career opportunities.
Browse courses on
Career Development
Show steps
Show steps
Show steps
- Search for upcoming webinars and conferences related to data analysis.
- Register and attend the events.
- Connect with speakers and attendees to learn about their experiences.
Develop a Statistical Model for a Real-World Problem
Show steps
Apply your statistical knowledge to a practical problem, deepening your understanding and developing your problem-solving abilities.
Browse courses on
Statistical Modeling
Show steps
Show steps
Show steps
- Identify a real-world dataset related to your field of interest.
- Clean and prepare the dataset for analysis.
- Develop and evaluate statistical models to uncover insights.
- Present your findings and make recommendations.
Career center
Learners who complete Data Driven Decision Making will develop knowledge and skills
that may be useful to these careers:
Data Scientist
Data Scientist
Data Scientists use data to build models and solve business problems. This course can help you develop the skills needed to be successful in this role by teaching you how to perform statistical analyses, interpret data, and build models.
Data Analyst
Data Analyst
Data Analysts are responsible for collecting, cleaning, and analyzing data to help businesses make informed decisions. This course can help you develop the skills needed to be successful in this role by teaching you how to perform statistical analyses and interpret data.
Statistician
Statistician
Statisticians collect, analyze, and interpret data to help businesses make informed decisions. This course can help you develop the skills needed to be successful in this role by teaching you how to perform statistical analyses, interpret data, and communicate your findings.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use data to build models and solve business problems. This course can help you develop the skills needed to be successful in this role by teaching you how to perform statistical analyses and interpret data.
Actuary
Actuary
Actuaries use data to assess risk and make informed decisions. This course can help you develop the skills needed to be successful in this role by teaching you how to perform statistical analyses and interpret data.
Business Analyst
Business Analyst
Business Analysts use data to help businesses make informed decisions. This course can help you develop the skills needed to be successful in this role by teaching you how to perform statistical analyses and interpret data.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts use data to improve the efficiency of business operations. This course can help you develop the skills needed to be successful in this role by teaching you how to perform statistical analyses and interpret data.
Epidemiologist
Epidemiologist
Epidemiologists collect, analyze, and interpret data to study the distribution and causes of disease. This course can help you develop the skills needed to be successful in this role by teaching you how to perform statistical analyses and interpret data.
Biostatistician
Biostatistician
Biostatisticians use data to design and analyze clinical trials and other health-related studies. This course can help you develop the skills needed to be successful in this role by teaching you how to perform statistical analyses and interpret data.
Market Researcher
Market Researcher
Market Researchers collect, analyze, and interpret data to help businesses understand their customers and make informed decisions. This course can help you develop the skills needed to be successful in this role by teaching you how to perform statistical analyses and interpret data.
Civil Engineer
Civil Engineer
Civil Engineers design and build infrastructure. This course may be useful in this role by teaching you how to perform statistical analyses and interpret data, which can be useful in designing and building infrastructure.
Computer Engineer
Computer Engineer
Computer Engineers design and build computers and computer systems. This course may be useful in this role by teaching you how to perform statistical analyses and interpret data, which can be useful in designing and building computers and computer systems.
Software Engineer
Software Engineer
Software Engineers design and build software. This course may be useful in this role by teaching you how to perform statistical analyses and interpret data, which can be useful in designing and building software.
Mechanical Engineer
Mechanical Engineer
Mechanical Engineers design and build machines. This course may be useful in this role by teaching you how to perform statistical analyses and interpret data, which can be useful in designing and building machines.
Electrical Engineer
Electrical Engineer
Electrical Engineers design and build electrical systems. This course may be useful in this role by teaching you how to perform statistical analyses and interpret data, which can be useful in designing and building electrical systems.
For more career information including salaries, visit:
OpenCourser.com/course/0mghlg/data
Reading list
We've selected eight 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
Data Driven Decision Making.
Provides a comprehensive introduction to data analysis and statistical learning. It covers the basics of data analysis, supervised learning, and unsupervised learning.
Provides a comprehensive introduction to data mining for business intelligence. It covers the basics of data mining, data mining algorithms, and data mining applications.
Provides a comprehensive introduction to statistical methods for the social sciences. It covers the basics of statistics, including probability, estimation, hypothesis testing, and regression analysis.
Provides a comprehensive introduction to statistical methods for management and economics. It covers the basics of statistics, including probability, estimation, hypothesis testing, and regression analysis.
Provides a comprehensive introduction to statistics for psychology. It covers the basics of statistics, including probability, estimation, hypothesis testing, and regression analysis.
Provides a practical guide to using R for statistical analysis. It covers the basics of R programming, statistical analysis, and data visualization.
Save
Provides a practical guide to using R for data analysis. It covers the basics of R programming, data analysis, and data visualization.
Provides an introduction to the principles and practices of statistical quality control. It covers the basics of sampling, process control, and data analysis.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/0mghlg/data
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Level
Intermediate
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
- Data Driven Decision Making (viewing)
- Data Acquisition, Risk, and Estimation
Good to know
Taught by Wendy Martin, who is recognized for their work in engineering management
Meant for engineers and business professionals who need help choosing appropriate statistical tests
Introduces one sample tests for comparison to historical data
Presents two sample tests for both independent and dependent data
Features the Analysis of Variance for analyzing data with more than two groups
Students will need access to RStudio and ROIStat software
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