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Richard Valliant, Ph.D.
In this course you will learn how to use survey weights to estimate descriptive statistics, like means and totals, and more complicated quantities like model parameters for linear and logistic regressions. Software capabilities will be covered with R® receiving particular emphasis. The course will also cover the basics of record linkage and statistical matching—both of which are becoming more important as ways of combining data from different sources. Combining of datasets raises ethical issues which the course reviews. Informed consent may have to be obtained from persons to allow their data to be linked. You will learn about differences in the legal requirements in different countries.
Register for this course and see more details by visiting:
OpenCourser.com/course/9l4pcf/combining
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What's inside
Syllabus
Basic Estimation
After completing Modules 1 and 2 of this course you will understand how to estimate descriptive statistics, overall and for subgroups, when you deal with survey data. We will review software for estimation (R, Stata, SAS) with examples for how to estimate things like means, proportions, and totals. You will also learn how to estimate parameters in linear, logistic, and other models and learn software options with emphasis on R. Module 3 and 4 discuss how you can add additional data to your analysis. This requires knowing about record linkage techniques, and what it takes to get permission to link data.
Read more
Syllabus
Basic Estimation
After completing Modules 1 and 2 of this course you will understand how to estimate descriptive statistics, overall and for subgroups, when you deal with survey data. We will review software for estimation (R, Stata, SAS) with examples for how to estimate things like means, proportions, and totals. You will also learn how to estimate parameters in linear, logistic, and other models and learn software options with emphasis on R. Module 3 and 4 discuss how you can add additional data to your analysis. This requires knowing about record linkage techniques, and what it takes to get permission to link data.
Read more
Models
Module 2 covers how to estimate linear and logistic model parameters using survey data. After completing this module, you will understand how the methods used differ from the ones for non-survey data. We also cover the features of survey data sets that need to be accounted for when estimating standard errors of estimated model parameters.
Record Linkage
Module starts with the current debate on using more (linked) administrative records in the U.S. Federal Statistical System, and a general motivation for linking records. Several examples will be given on why it is useful to link data. Challenges of record linkage will be discussed. A brief overview over key linkage techniques is included as well.
Ethics
This module will discuss key issues in obtaining consent to record linkage. Failure to consent can lead to bias estimates. Current research examples will be given as well as practical suggestions on how to obtain linkage consent.
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Introduces survey weights, which are essential for accurately estimating population parameters from sample data
Covers basic estimation techniques for means, proportions, and totals, as well as more advanced methods for linear and logistic regressions
Emphasizes the use of R software, which is widely used in survey analysis
Provides a comprehensive overview of record linkage and statistical matching techniques
Addresses ethical issues related to data linkage and informed consent, ensuring responsible data handling
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Reviews summary
Well-received course: complex data
Learners say that this course is well received and is useful and informative. The lectures make complex topics clear and understandable, and the professors are knowledgeable.
The instructors make complex topics easy to understand.
"Teachers made complex topics clear and understandable."
"The instructional material that are very poor and nearly immpossible to follow. The courses in this specialisation run by other instructors are much better."
This course is well-liked by students.
"I liked the practical examples"
"Great course!"
"The course was useful and informative to me."
This course may be difficult for some students.
"I don't feel like I am learning enough, and I do not have the confidence I thought I would when I saw the course."
"The instructional material that are very poor and nearly immpossible to follow."
Some instructors are better than others.
"The good part of the course is the one dealt with by Frauke Kreuter."
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 Combining and Analyzing Complex Data with these
activities:
Review an R data analysis textbook
Show steps
Reviewing an R data analysis textbook will help you brush up on your R skills and refresh your knowledge of data analysis concepts, which will be essential for success in this course.
View
Hands-On Programming with R: Write Your Own...
on Amazon
Show steps
-
Choose a textbook that covers the topics you need to review.
-
Read through the textbook, taking notes on the key concepts.
-
Complete the practice exercises in the textbook to test your understanding.
Review a book on survey sampling
Show steps
Reviewing a book on survey sampling will help you understand the different types of sampling methods and how to design a survey that will produce valid results.
View
Sampling: Design and Analysis (Chapman &...
on Amazon
Show steps
-
Choose a book on survey sampling that covers the topics you need to review.
-
Read through the book, taking notes on the key concepts.
-
Complete the practice exercises in the book to test your understanding.
Practice estimating means and totals using survey data
Show steps
Practicing estimating means and totals using survey data will help you develop the skills you need to complete the assignments and projects in this course.
Browse courses on
Survey Data Analysis
Show steps
-
Find a dataset that contains survey data.
-
Use R to estimate the mean and total for a variable in the dataset.
-
Compare your results to the results obtained using other software, such as Stata or SAS.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Practice estimating model parameters using survey data
Show steps
Practicing estimating model parameters using survey data will help you develop the skills you need to complete the assignments and projects in this course.
Browse courses on
Survey Data Analysis
Show steps
-
Find a dataset that contains survey data.
-
Use R to estimate the parameters of a linear or logistic regression model using the survey data.
-
Compare your results to the results obtained using other software, such as Stata or SAS.
Follow a tutorial on using R for record linkage
Show steps
Following a tutorial on using R for record linkage will help you learn how to combine data from different sources, which is a valuable skill for data analysts.
Browse courses on
Record Linkage
Show steps
-
Find a tutorial on using R for record linkage.
-
Follow the steps in the tutorial to learn how to link records.
-
Apply what you have learned to a real-world dataset.
Follow a tutorial on record linkage in R
Show steps
Following a tutorial on record linkage in R will help you learn how to combine data from different sources, which is a valuable skill for data analysts.
Browse courses on
Record Linkage
Show steps
-
Find a tutorial on record linkage in R.
-
Follow the steps in the tutorial to learn how to link records.
-
Apply what you have learned to a real-world dataset.
Create a presentation on the ethical issues of record linkage
Show steps
Creating a presentation on the ethical issues of record linkage will help you understand the importance of obtaining consent from individuals before linking their data.
Browse courses on
Ethics
Show steps
-
Research the ethical issues of record linkage.
-
Develop a presentation that outlines the ethical issues and how they can be addressed.
-
Present your presentation to a group of your peers.
Create a presentation on how to obtain consent for record linkage
Show steps
Creating a presentation on how to obtain consent for record linkage will help you understand the importance of informed consent and how to obtain it from individuals.
Browse courses on
Ethics
Show steps
-
Research the legal requirements for obtaining consent for record linkage in your country.
-
Develop a presentation that outlines the steps involved in obtaining consent.
-
Present your presentation to a group of your peers.
Review an R data analysis textbook
Show steps
Reviewing an R data analysis textbook will help you brush up on your R skills and refresh your knowledge of data analysis concepts, which will be essential for success in this course.
View
Hands-On Programming with R: Write Your Own...
on Amazon
Show steps
Show steps
Show steps
- Choose a textbook that covers the topics you need to review.
- Read through the textbook, taking notes on the key concepts.
- Complete the practice exercises in the textbook to test your understanding.
Review a book on survey sampling
Show steps
Reviewing a book on survey sampling will help you understand the different types of sampling methods and how to design a survey that will produce valid results.
View
Sampling: Design and Analysis (Chapman &...
on Amazon
Show steps
Show steps
Show steps
- Choose a book on survey sampling that covers the topics you need to review.
- Read through the book, taking notes on the key concepts.
- Complete the practice exercises in the book to test your understanding.
Practice estimating means and totals using survey data
Show steps
Practicing estimating means and totals using survey data will help you develop the skills you need to complete the assignments and projects in this course.
Browse courses on
Survey Data Analysis
Show steps
Show steps
Show steps
- Find a dataset that contains survey data.
- Use R to estimate the mean and total for a variable in the dataset.
- Compare your results to the results obtained using other software, such as Stata or SAS.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Practice estimating model parameters using survey data
Show steps
Practicing estimating model parameters using survey data will help you develop the skills you need to complete the assignments and projects in this course.
Browse courses on
Survey Data Analysis
Show steps
Show steps
Show steps
- Find a dataset that contains survey data.
- Use R to estimate the parameters of a linear or logistic regression model using the survey data.
- Compare your results to the results obtained using other software, such as Stata or SAS.
Follow a tutorial on using R for record linkage
Show steps
Following a tutorial on using R for record linkage will help you learn how to combine data from different sources, which is a valuable skill for data analysts.
Browse courses on
Record Linkage
Show steps
Show steps
Show steps
- Find a tutorial on using R for record linkage.
- Follow the steps in the tutorial to learn how to link records.
- Apply what you have learned to a real-world dataset.
Follow a tutorial on record linkage in R
Show steps
Following a tutorial on record linkage in R will help you learn how to combine data from different sources, which is a valuable skill for data analysts.
Browse courses on
Record Linkage
Show steps
Show steps
Show steps
- Find a tutorial on record linkage in R.
- Follow the steps in the tutorial to learn how to link records.
- Apply what you have learned to a real-world dataset.
Create a presentation on the ethical issues of record linkage
Show steps
Creating a presentation on the ethical issues of record linkage will help you understand the importance of obtaining consent from individuals before linking their data.
Browse courses on
Ethics
Show steps
Show steps
Show steps
- Research the ethical issues of record linkage.
- Develop a presentation that outlines the ethical issues and how they can be addressed.
- Present your presentation to a group of your peers.
Create a presentation on how to obtain consent for record linkage
Show steps
Creating a presentation on how to obtain consent for record linkage will help you understand the importance of informed consent and how to obtain it from individuals.
Browse courses on
Ethics
Show steps
Show steps
Show steps
- Research the legal requirements for obtaining consent for record linkage in your country.
- Develop a presentation that outlines the steps involved in obtaining consent.
- Present your presentation to a group of your peers.
Career center
Learners who complete Combining and Analyzing Complex Data will develop knowledge and skills
that may be useful to these careers:
Statistician
Statistician
As a Statistician, you will use statistical methods to analyze data and draw conclusions about the world around us. This course may be particularly helpful in helping you to understand how to use survey data to estimate descriptive statistics and model parameters.
Computer Scientist
Computer Scientist
As a Computer Scientist, you will design, develop, and implement computer software. This course may be particularly helpful in helping you to understand how to use R® to analyze complex data and combine datasets from different sources.
Machine Learning Engineer
Machine Learning Engineer
As a Machine Learning Engineer, you will design, develop, and implement machine learning models. This course may be particularly helpful in helping you to understand how to use R® to analyze complex data and combine datasets from different sources.
Data Analyst
Data Analyst
As a Data Analyst, you will use data to solve business problems and make informed decisions. This course may be particularly helpful in helping you to understand how to use R® to analyze complex data and combine datasets from different sources.
Artificial Intelligence Engineer
Artificial Intelligence Engineer
As an Artificial Intelligence Engineer, you will design, develop, and implement artificial intelligence systems. This course may be particularly helpful in helping you to understand how to use R® to analyze complex data and combine datasets from different sources.
Data Engineer
Data Engineer
As a Data Engineer, you will design, build, and maintain data pipelines. This course may be particularly helpful in helping you to understand how to use R® to analyze complex data and combine datasets from different sources.
Software Engineer
Software Engineer
As a Software Engineer, you will design, develop, and maintain software applications. This course may be particularly helpful in helping you to understand how to use R® to analyze complex data and combine datasets from different sources.
Actuary
Actuary
As an Actuary, you will use mathematical and statistical methods to assess risk and uncertainty. This course may be particularly helpful in helping you to understand how to use survey data to estimate descriptive statistics and more complicated quantities like model parameters for linear and logistic regressions.
Operations Research Analyst
Operations Research Analyst
As an Operations Research Analyst, you will use mathematical and statistical methods to improve the efficiency of organizations. This course may be particularly helpful in helping you to understand how to use survey data to estimate descriptive statistics and more complicated quantities like model parameters for linear and logistic regressions.
Market Research Analyst
Market Research Analyst
As a Market Research Analyst, you will collect, analyze, and interpret data about markets, products, and consumers. This course may be particularly helpful in helping you to understand how to use survey data to estimate descriptive statistics and more complicated quantities like model parameters for linear and logistic regressions.
Social Scientist
Social Scientist
As a Social Scientist, you will study human behavior and society. This course may be particularly helpful in helping you to understand how to use survey data to estimate descriptive statistics and more complicated quantities like model parameters for linear and logistic regressions.
Demographer
Demographer
As a Demographer, you will study the size, composition, and distribution of human populations. This course may be useful in helping you to understand how to use survey data to estimate descriptive statistics and more complicated quantities like model parameters for linear and logistic regressions.
Epidemiologist
Epidemiologist
As an Epidemiologist, you will study the distribution and determinants of health-related states or events in specified populations. This course may be useful in helping you to understand how to use survey data to estimate descriptive statistics and more complicated quantities like model parameters for linear and logistic regressions.
Financial Analyst
Financial Analyst
As a Financial Analyst, you will use financial data to make investment recommendations. This course may be useful in helping you to understand how to use survey data to estimate descriptive statistics and more complicated quantities like model parameters for linear and logistic regressions.
Survey Researcher
Survey Researcher
As a Survey Researcher, you will design, conduct, and analyze surveys to collect data on a variety of topics. This course may be useful in helping you to understand how to use survey weights to estimate descriptive statistics and more complicated quantities like model parameters for linear and logistic regressions.
For more career information including salaries, visit:
OpenCourser.com/course/9l4pcf/combining
Reading list
We've selected 15 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
Combining and Analyzing Complex Data.
Provides a comprehensive overview of the algorithmic foundations of differential privacy, a technique for protecting the privacy of individuals in data analysis. It valuable resource for researchers and practitioners who want to learn about the latest advances in differential privacy.
Provides an in-depth treatment of the analysis of complex survey data, including topics such as sampling weights, design effects, and variance estimation. It valuable resource for researchers and practitioners who work with complex survey data.
Provides a comprehensive overview of the theory and practice of Bayesian data analysis. It valuable resource for researchers and practitioners who want to learn about the latest advances in Bayesian data analysis.
Provides a comprehensive overview of the principles of causal inference. It valuable resource for researchers and practitioners who want to learn about the latest advances in causal inference.
Save
This comprehensive book provides a thorough foundation in sampling theory and methods. It valuable reference for students and professionals in statistics, survey research, and data analysis.
Provides a comprehensive overview of the techniques for making black box machine learning models explainable. It valuable resource for researchers, practitioners, and policymakers who want to understand the ethical implications of AI.
Provides a comprehensive overview of the theory and practice of econometrics. It valuable resource for researchers and practitioners who want to learn about the latest advances in econometrics.
Save
Provides a comprehensive overview of statistical methods for survey research, including topics such as sampling, estimation, and hypothesis testing. It valuable resource for researchers and practitioners who design and conduct surveys.
Provides a comprehensive overview of statistical learning methods, including topics such as supervised learning, unsupervised learning, and model selection. It valuable resource for researchers and practitioners who want to learn about the latest advances in statistical learning.
Provides a comprehensive overview of machine learning methods, including topics such as supervised learning, unsupervised learning, and model selection. It valuable resource for researchers and practitioners who want to apply machine learning to real-world problems.
Save
A guide to using causal inference methods to estimate the effects of interventions and policies. It covers a wide range of methods, including regression discontinuity designs, instrumental variables, and difference-in-differences.
A textbook on statistical thinking, covering the basics of statistical inference and the use of statistics to solve problems. It includes a discussion of the ethical issues involved in the use of statistics.
A textbook on Python for data analysis, covering the basics of Python as well as the use of Python for data cleaning, analysis, and visualization. It includes a discussion of the ethical issues involved in working with data.
Save
A textbook on R for data science, covering the basics of R as well as the use of R for data cleaning, analysis, and visualization. It includes a discussion of the ethical issues involved in working with data.
A textbook on Power BI for data analysis, covering the basics of Power BI as well as the use of Power BI for data cleaning, analysis, and visualization. It includes a discussion of the ethical issues involved in working with data.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/9l4pcf/combining
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Coursera
Institution
University of Maryland, College Park
Instructor
Richard Valliant, Ph.D.
Language
English
Transcripts
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آذربایجان دیلی
This course belongs to a
collection
called
Survey Data Collection and Analytics . It's comprised of seven courses:
- Dealing With Missing Data
- Framework for Data Collection and Analysis
- Combining and Analyzing Complex Data (viewing)
- Questionnaire Design for Social Surveys
- Sampling People, Networks and Records
- Survey Data Collection and Analytics Project (Capstone)
- Data Collection: Online, Telephone and Face-to-face
Good to know
Introduces survey weights, which are essential for accurately estimating population parameters from sample data
Covers basic estimation techniques for means, proportions, and totals, as well as more advanced methods for linear and logistic regressions
Emphasizes the use of R software, which is widely used in survey analysis
Provides a comprehensive overview of record linkage and statistical matching techniques
Addresses ethical issues related to data linkage and informed consent, ensuring responsible data handling
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