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NHANES 2017-2022 data was used to build and compare two linear regression models predicting HDL cholesterol in females ages 30 - 55.

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Possible-Predictors-of-HDL-Cholesterol-in-Adult-Females

Part II of the second data science project completed for Statistical Methods I. National Health & Nutrition Examination Survey 2017-2022 (NHANES 2017-2022) data was used to build and compare two linear regression models predicting HDL cholesterol in females ages 30 - 55.

Skills Demonstrated:

  • Clean data set, investigating and making appropriate decisions about missing data
  • Create well-labeled and attractive visualizations of outcome, investigating potential transformations of that outcome
  • Define a research question related to how effectively your key predictor predicts your quantitative outcome, while (possibly) adjusting for the other predictors
  • Develop two competitive linear regression models - one with key predictor and another with additional predictors
  • Use statistical model to make predictions and assess the quality of those predictions
  • Assess model performance including predictive performance, adherence to assumptions, and predictive quality
  • Describe study limitations and next steps

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NHANES 2017-2022 data was used to build and compare two linear regression models predicting HDL cholesterol in females ages 30 - 55.

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