Introduction and Maximizing Validity and Data Origin Quality-Welcome!
Welcome to Course 3 and the final course in the Specialization!
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Course Syllabus
Course Pre-Survey
Introduction and Maximizing Validity and Data Origin Quality-Validity
Maximizing Validity for Designed Data
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Case Study: Improving Questions Based on Pre-Testing Results
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Maximizing Validity for Gathered Data
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Case Study pre-read: Improving Google Flu Trends Estimates for the United States through Transformation
Case Study: Improving the Validity of Gathered Data using Auxiliary Data and Transformations
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Introduction and Maximizing Validity and Data Origin Quality-Data Origin
Maximizing Data Origin Quality for Designed Data
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Case Study: Standardized vs. Conversational Interviewing
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Maximizing Data Original Quality for Gathered Data
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Optional: links from previous lecture on Maximizing Data Original Quality for Gathered Data
Case Study: Simple Lessons Learned for Improving Data Origin Quality While Web Scraping
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Maximizing Processing and Data Access Quality-Processing
Maximizing Processing Quality for Designed Data
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Example: Double Data Entry and Imputation to Maximize Data Processing Quality
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Maximizing Processing Quality for Gathered Data
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Files for the next example
Example: Maximizing Processing Quality for Gathered Data
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Maximizing Processing and Data Access Quality-Data Access
Maximizing Data Access Quality for Designed Data
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Exploring and Evaluating Enhancements for ABS Sampling Frames
Maximizing Data Access Quality for Gathered Data
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Example: Maximizing Data Access Quality for Gathered Data
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Maximizing Data Source Quality and Minimizing Data Missingness-Data Source
Maximizing Data Source Quality for Designed Data
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Example: Maximizing Data Source Quality for Designed Data
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Maximizing Data Source Quality for Gathered Data
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Probability Samples of Twitter
Maximizing Data Source Quality and Minimizing Data Missingness-Data Missingness
Minimizing Data Missingness for Designed Data
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Files for next example
Example: Imputation and Weighting Adjustment
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Minimizing Data Missingness for Designed Data: Responsive and Adaptive Survey Design
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Optional: .csv and .py files for the next lecture
Minimizing Data Missingness for Gathered Data
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Example: Minimizing Data Missingness for Gathered Data
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Maximizing the Quality of Data Analysis-Maximizing the Quality of Data Analysis
Maximizing the Quality of an Analysis of Designed Data
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Case Studies in Analytic Error
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Maximizing the Quality of an Analysis of Gathered Data
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Case Study: Maximizing the Quality of an Analysis of Video Image Data
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Maximizing the Quality of Data Analysis-Course and Specialization Conclusion
Course and Specialization Conclusion
References for Design Strategies for Maximizing Total Data Quality
Course and Specialization Post-Survey