Modules
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Learn the basics of RStudio, R packages, and the structure of the GSS dataset.
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02. Introduction to data and scripting
Build core research and data vocabulary while learning how to work with R scripts efficiently.
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Run and interpret frequency tables, descriptive tables, bar graphs, and histograms.
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Learn why variables are recoded and how to merge or reverse categories correctly.
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Create new variables and index measures while avoiding common computing mistakes.
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Learn how to run chi-square tests and interpret statistical significance for categorical variables.
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Compare group means with t-tests and interpret the results clearly.
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Learn key sampling concepts and the difference between probability and non-probability sampling.
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Create and customize stacked bar graphs for variables and groups.
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Learn the basics of correlation and how to conduct and interpret correlation analysis.
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Begin linear regression by learning what it does and how to read its main results.
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Create dummy variables and use them correctly in linear regression models.
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13. Logistic regression basics
Learn when logistic regression is appropriate and how to interpret odds ratios and related outputs.
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Practice modeling by applying logistic regression in guided exercises.
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15. Regression assumptions and diagnostics
Learn key regression assumptions and diagnose problems such as heteroscedasticity.