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James M Lepkowski
Good data collection is built on good samples. But the samples can be chosen in many ways. Samples can be haphazard or convenient selections of persons, or records, or networks, or other units, but one questions the quality of such samples, especially what these selection methods mean for drawing good conclusions about a population after data collection and analysis is done. Samples can be more carefully selected based on a researcher’s judgment, but one then questions whether that judgment can be biased by personal factors. Samples can also be draw in statistically rigorous and careful ways, using random selection and control methods to provide sound representation and cost control. It is these last kinds of samples that will be discussed in this course. We will examine simple random sampling that can be used for sampling persons or records, cluster sampling that can be used to sample groups of persons or records or networks, stratification which can be applied to simple random and cluster samples, systematic selection, and stratified multistage samples. The course concludes with a brief overview of how to estimate and summarize the uncertainty of randomized sampling.
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What's inside
Syllabus
Module 1: Sampling as a research tool
Mere randomization
Saving money using cluster sampling
Read more
Syllabus
Module 1: Sampling as a research tool
Mere randomization
Saving money using cluster sampling
Read more
Using auxiliary data to be more efficient
Simplified sampling
Pulling it all together
Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Introduces the basics of random sampling in a straightforward manner, which is appropriate for beginners just getting started with the topic
Ideal for those who want to improve their understanding of probability and statistics as it is used in research
Taught by Dr. James M. Lepkowski, a respected researcher in the field of survey methodology
Intermediate-level learners will find this course particularly valuable for gaining a deeper understanding of sampling techniques
Covers essential concepts such as simple random sampling, cluster sampling, and stratified multistage samples, which are widely used in various research settings
Provides a solid foundation for learners who want to pursue advanced studies or engage in research involving sampling methodologies
Save this course
Save Sampling People, Networks and Records to your list so you can find it easily later:
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Reviews summary
Well-received course on sampling techniques
learners say this well-received course provides engaging assignments that enable students to develop solid foundations of sampling techniques. Students appreciate the expert presentation and find the content to be comprehensive. However, some students report that the course is difficult and requires a strong mathematical background.
assignments help students learn
"good way to learn new skills"
"Best course of the specialization. Great instructor."
"I was very impressed with the course content as well as the expert presentation. This course has empowered with relevant and practical sampling skills that I will apply in the my work"
instructor is engaging and knowledgeable
"Very effective instructor who talks as if he's actually in class with you, rather than reading from slides. "
"I gained solid foundations of sampling techniques from this course. The instructor is excellent, and the course content is very comprehensive."
"Comprehensive Knowledge is provided in the course. Highly skilled faculty member."
course is challenging, especially for beginners
"It is a tough course, but I learned so much"
"Poorly delivered, disorganized, no clear explanations of mathematics needed, caters more to solely auditory learners (very few and mostly unhelpful visuals)."
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 Sampling People, Networks and Records with these
activities:
Sampling: Statistical Methods and Applications
Show steps
Supplement course material with an in-depth reference on sampling theory and methods.
Show steps
-
Read chapters on different sampling methods.
-
Work through examples and exercises.
-
Apply concepts to real-world sampling scenarios.
Review statistics
Show steps
Refresh statistical concepts and techniques to strengthen understanding of sampling fundamentals.
Browse courses on
Statistics
Show steps
-
Revisit concepts of probability and distributions.
-
Practice solving problems related to sampling distributions.
-
Review hypothesis testing and confidence intervals.
Sampling simulation exercises
Show steps
Engage in hands-on simulations to reinforce sampling concepts and understand the impact of sample size.
Browse courses on
Sampling Techniques
Show steps
-
Simulate sampling from different populations.
-
Analyze the effect of sample size on accuracy and precision.
-
Experiment with different sampling methods.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Sampling Design Discussion Group
Show steps
Engage in peer discussions to exchange ideas, perspectives, and experiences related to sampling design.
Show steps
-
Join a study group or forum.
-
Participate in discussions on sampling strategies.
-
Share insights and provide feedback to peers.
Exploratory Data Analysis using Python
Show steps
Learn practical skills for visualizing and analyzing data, enhancing understanding of sampling results.
Browse courses on
Python
Show steps
-
Install Python and necessary libraries.
-
Explore datasets and perform basic data cleaning.
-
Visualize data using plots and charts.
Sampling Infographic
Show steps
Create a visual representation of sampling concepts to reinforce understanding and share knowledge.
Show steps
-
Identify key concepts and principles of sampling.
-
Design an infographic that visually explains these concepts.
-
Share the infographic with peers or a wider audience.
Sampling Plan Presentation
Show steps
Develop a comprehensive sampling plan and present it, solidifying understanding and communication skills.
Browse courses on
Sampling Design
Show steps
-
Choose a research question and define target population.
-
Select appropriate sampling method and justify choice.
-
Determine sample size and sampling frame.
-
Develop a detailed sampling protocol.
-
Present findings and recommendations to stakeholders.
Data Collection Project
Show steps
Design and implement a data collection project using appropriate sampling techniques, applying knowledge to a real-world scenario.
Show steps
-
Define research question and identify target population.
-
Develop a sampling plan and collect data.
-
Analyze data and draw conclusions.
-
Present findings and discuss implications.
Sampling: Statistical Methods and Applications
Show steps
Supplement course material with an in-depth reference on sampling theory and methods.
Show steps
Show steps
Show steps
- Read chapters on different sampling methods.
- Work through examples and exercises.
- Apply concepts to real-world sampling scenarios.
Review statistics
Show steps
Refresh statistical concepts and techniques to strengthen understanding of sampling fundamentals.
Browse courses on
Statistics
Show steps
Show steps
Show steps
- Revisit concepts of probability and distributions.
- Practice solving problems related to sampling distributions.
- Review hypothesis testing and confidence intervals.
Sampling simulation exercises
Show steps
Engage in hands-on simulations to reinforce sampling concepts and understand the impact of sample size.
Browse courses on
Sampling Techniques
Show steps
Show steps
Show steps
- Simulate sampling from different populations.
- Analyze the effect of sample size on accuracy and precision.
- Experiment with different sampling methods.
Five other activities
Expand to see all activities and additional details
Show all eight activities
Sampling Design Discussion Group
Show steps
Engage in peer discussions to exchange ideas, perspectives, and experiences related to sampling design.
Show steps
Show steps
Show steps
- Join a study group or forum.
- Participate in discussions on sampling strategies.
- Share insights and provide feedback to peers.
Exploratory Data Analysis using Python
Show steps
Learn practical skills for visualizing and analyzing data, enhancing understanding of sampling results.
Browse courses on
Python
Show steps
Show steps
Show steps
- Install Python and necessary libraries.
- Explore datasets and perform basic data cleaning.
- Visualize data using plots and charts.
Sampling Infographic
Show steps
Create a visual representation of sampling concepts to reinforce understanding and share knowledge.
Show steps
Show steps
Show steps
- Identify key concepts and principles of sampling.
- Design an infographic that visually explains these concepts.
- Share the infographic with peers or a wider audience.
Sampling Plan Presentation
Show steps
Develop a comprehensive sampling plan and present it, solidifying understanding and communication skills.
Browse courses on
Sampling Design
Show steps
Show steps
Show steps
- Choose a research question and define target population.
- Select appropriate sampling method and justify choice.
- Determine sample size and sampling frame.
- Develop a detailed sampling protocol.
- Present findings and recommendations to stakeholders.
Data Collection Project
Show steps
Design and implement a data collection project using appropriate sampling techniques, applying knowledge to a real-world scenario.
Show steps
Show steps
Show steps
- Define research question and identify target population.
- Develop a sampling plan and collect data.
- Analyze data and draw conclusions.
- Present findings and discuss implications.
Career center
Learners who complete Sampling People, Networks and Records will develop knowledge and skills
that may be useful to these careers:
Researcher
Researcher
Researchers are responsible for conducting research studies, analyzing data, and writing reports. This course can help Researchers by providing them with the skills needed to design and conduct research studies, select samples, and analyze data. Additionally, the course can help Researchers to develop a strong foundation in research methods, which is essential for any researcher who wants to be successful in their field.
Data Analyst
Data Analyst
Data Analysts are responsible for collecting, analyzing, and interpreting data. This course can help Data Analysts by providing them with the skills needed to select samples, collect data, and analyze data. Additionally, the course can help Data Analysts to develop a strong foundation in data analysis methods, which is essential for any Data Analyst who wants to be successful in their field.
Statistician
Statistician
Statisticians are responsible for developing and using statistical methods to collect, analyze, and interpret data. This course can help Statisticians by providing them with the skills needed to design and conduct research studies, select samples, and analyze data. Additionally, the course can help Statisticians to develop a strong foundation in statistical methods, which is essential for any Statistician who wants to be successful in their field.
Survey Researcher
Survey Researcher
Survey Researchers are responsible for designing, conducting, and analyzing surveys. This course can help Survey Researchers by providing them with the skills needed to design and conduct surveys, select samples, and analyze data. Additionally, the course can help Survey Researchers to develop a strong foundation in survey research methods, which is essential for any Survey Researcher who wants to be successful in their field.
Market Researcher
Market Researcher
Market Researchers are responsible for conducting research on markets and consumers. This course can help Market Researchers by providing them with the skills needed to design and conduct research studies, select samples, and analyze data. Additionally, the course can help Market Researchers to develop a strong foundation in market research methods, which is essential for any Market Researcher who wants to be successful in their field.
Public Opinion Researcher
Public Opinion Researcher
Public Opinion Researchers are responsible for conducting research on public opinion. This course can help Public Opinion Researchers by providing them with the skills needed to design and conduct research studies, select samples, and analyze data. Additionally, the course can help Public Opinion Researchers to develop a strong foundation in public opinion research methods, which is essential for any Public Opinion Researcher who wants to be successful in their field.
Social Researcher
Social Researcher
Social Researchers are responsible for conducting research on social issues. This course can help Social Researchers by providing them with the skills needed to design and conduct research studies, select samples, and analyze data. Additionally, the course can help Social Researchers to develop a strong foundation in social research methods, which is essential for any Social Researcher who wants to be successful in their field.
Health Researcher
Health Researcher
Health Researchers are responsible for conducting research on health issues. This course can help Health Researchers by providing them with the skills needed to design and conduct research studies, select samples, and analyze data. Additionally, the course can help Health Researchers to develop a strong foundation in health research methods, which is essential for any Health Researcher who wants to be successful in their field.
Education Researcher
Education Researcher
Education Researchers are responsible for conducting research on education issues. This course can help Education Researchers by providing them with the skills needed to design and conduct research studies, select samples, and analyze data. Additionally, the course can help Education Researchers to develop a strong foundation in education research methods, which is essential for any Education Researcher who wants to be successful in their field.
Business Analyst
Business Analyst
Business Analysts are responsible for analyzing business data and making recommendations to improve business performance. This course may be useful for Business Analysts by providing them with the skills needed to select samples, collect data, and analyze data. Additionally, the course may help Business Analysts to develop a strong foundation in data analysis methods, which may be helpful for success in this field.
Financial Analyst
Financial Analyst
Financial Analysts are responsible for analyzing financial data and making recommendations to investors. This course may be useful for Financial Analysts by providing them with the skills needed to select samples, collect data, and analyze data. Additionally, the course may help Financial Analysts to develop a strong foundation in data analysis methods, which may be helpful for success in this field.
Operations Research Analyst
Operations Research Analyst
Operations Research Analysts are responsible for using mathematical and analytical techniques to improve the efficiency of business operations. This course may be useful for Operations Research Analysts by providing them with the skills needed to select samples, collect data, and analyze data. Additionally, the course may help Operations Research Analysts to develop a strong foundation in data analysis methods, which may be helpful for success in this field.
Software Engineer
Software Engineer
Software Engineers are responsible for designing, developing, and testing software systems. This course may be useful for Software Engineers by providing them with the skills needed to select samples, collect data, and analyze data. Additionally, the course may help Software Engineers to develop a strong foundation in data analysis methods, which may be helpful for success in this field.
Web Developer
Web Developer
Web Developers are responsible for designing and developing websites. This course may be useful for Web Developers by providing them with the skills needed to select samples, collect data, and analyze data. Additionally, the course may help Web Developers to develop a strong foundation in data analysis methods, which may be helpful for success in this field.
Database Administrator
Database Administrator
Database Administrators are responsible for managing and maintaining databases. This course may be useful for Database Administrators by providing them with the skills needed to select samples, collect data, and analyze data. Additionally, the course may help Database Administrators to develop a strong foundation in data analysis methods, which may be helpful for success in this field.
For more career information including salaries, visit:
OpenCourser.com/course/jgcx3m/sampling
Reading list
We've selected seven 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
Sampling People, Networks and Records.
Save
A comprehensive textbook on sampling methods and their applications in various fields, provides a theoretical foundation and practical guidance on designing and analyzing surveys.
A collection of advanced topics in survey research, including chapters on new sampling methods and data collection techniques.
Save
A highly technical and mathematical treatment of sampling theory, covers advanced topics such as optimal sample design, non-response bias, and robust estimation.
A specialized text on sampling methods for network data, covers topics such as snowball sampling, referral sampling, and ego networks.
Save
A technical book on statistical methods for analyzing network data, covers topics such as network visualization, centrality measures, and inferential statistics.
A comprehensive handbook on social network analysis, includes chapters on sampling methods for network data.
A general textbook on statistical inference, provides background on probability theory and hypothesis testing, which are fundamental concepts in sampling.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/jgcx3m/sampling
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Level
Introductory
Via
Coursera
Institution
University of Michigan
Instructor
James M Lepkowski
Language
English
Transcripts
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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
- Questionnaire Design for Social Surveys
- Sampling People, Networks and Records (viewing)
- Survey Data Collection and Analytics Project (Capstone)
- Data Collection: Online, Telephone and Face-to-face
Good to know
Introduces the basics of random sampling in a straightforward manner, which is appropriate for beginners just getting started with the topic
Ideal for those who want to improve their understanding of probability and statistics as it is used in research
Taught by Dr. James M. Lepkowski, a respected researcher in the field of survey methodology
Intermediate-level learners will find this course particularly valuable for gaining a deeper understanding of sampling techniques
Covers essential concepts such as simple random sampling, cluster sampling, and stratified multistage samples, which are widely used in various research settings
Provides a solid foundation for learners who want to pursue advanced studies or engage in research involving sampling methodologies
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