University of Maryland, College Park
Combining and Analyzing Complex Data
University of Maryland, College Park

Combining and Analyzing Complex Data

This course is part of Survey Data Collection and Analytics Specialization

Taught in English

Some content may not be translated

8,393 already enrolled

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Course

Gain insight into a topic and learn the fundamentals

4.1

(58 reviews)

9 hours (approximately)
Flexible schedule
Learn at your own pace

Details to know

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Assessments

4 quizzes

Course

Gain insight into a topic and learn the fundamentals

4.1

(58 reviews)

9 hours (approximately)
Flexible schedule
Learn at your own pace

See how employees at top companies are mastering in-demand skills

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Build your subject-matter expertise

This course is part of the Survey Data Collection and Analytics Specialization
When you enroll in this course, you'll also be enrolled in this Specialization.
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There are 4 modules in this course

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.

What's included

7 videos6 readings1 quiz

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.

What's included

8 videos8 readings1 quiz

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.

What's included

4 videos12 readings1 quiz1 discussion prompt

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.

What's included

5 videos3 readings1 quiz

Instructor

Instructor ratings
3.8 (5 ratings)
Richard Valliant, Ph.D.
University of Maryland, College Park
5 Courses16,031 learners

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4.1

58 reviews

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AA
5

Reviewed on Feb 11, 2021

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