Previous Next Step Data Analysis in R Data Analysis in R: Orientation Learning Objectives 15-20 minutes Applied Step 1 of 2 Flip Cards Learning Objectives 1 / 2 Flip Cards Learning Objectives Listen Objective 1 Explain the role of descriptive analysis in clinical research data management and reporting. Objective 2 Distinguish between data management summaries, monitoring summaries, and statistical analysis outputs. Objective 3 Generate descriptive summaries for categorical variables using counts and percentages. Objective 4 Generate descriptive summaries for numeric variables using appropriate measures of location and spread. Objective 5 Create cross-tabulations for site, visit, outcome, and data quality monitoring. Objective 6 Use R to produce reproducible summary tables suitable for review and reporting. Objective 7 Interpret summary outputs cautiously, with attention to missing data, denominators, coding, and study context. Objective 8 Identify common errors in descriptive analysis workflows and apply practical safeguards. Previous Lesson Next Step
Flip Cards Learning Objectives Listen Objective 1 Explain the role of descriptive analysis in clinical research data management and reporting. Objective 2 Distinguish between data management summaries, monitoring summaries, and statistical analysis outputs. Objective 3 Generate descriptive summaries for categorical variables using counts and percentages. Objective 4 Generate descriptive summaries for numeric variables using appropriate measures of location and spread. Objective 5 Create cross-tabulations for site, visit, outcome, and data quality monitoring. Objective 6 Use R to produce reproducible summary tables suitable for review and reporting. Objective 7 Interpret summary outputs cautiously, with attention to missing data, denominators, coding, and study context. Objective 8 Identify common errors in descriptive analysis workflows and apply practical safeguards.