Choosing a dataset for linear regression depends on your research question and the availability of relevant variables. Datasets with continuous dependent variables and numeric independent variables are ideal. Consider datasets like housing prices with predictors such as square footage, crime rates, or location; stock prices with factors like volume traded and economic indicators; or academic performance with predictors like study hours and GPA. Ensure the dataset is clean, suitably big, and reflects the population of interest. Public repositories like Kaggle, UCI Machine Learning Repository, or government databases often offer diverse datasets suitable for linear regression analysis.
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