Simple Linear Regression with a Binary (or Nominal Categorical) Predictor - Simple Regression

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Simple Linear Regression with a Binary (or Nominal Categorical) Predictor - Simple Regression Analysis in Public Health
Biostatistics in Public Health Specialization
Biostatistics is the application of statistical reasoning to the life sciences, and it's the key to unlocking the data gathered by researchers and the evidence presented in the scientific public health literature. In this course, we'll focus on the use of simple regression methods to determine the relationship between an outcome of interest and a single predictor via a linear equation. Along the way, you'll be introduced to a variety of methods, and you'll practice interpreting data and performing calculations on real data from published studies. Topics include logistic regression, confidence intervals, p-values, Cox regression, confounding, adjustment, and effect modification.
P-Value, Proportional Hazards Model, Confounding, regression
Thank you so much for a beautiful explanation and presentation of topics that a lot of physicians tend struggle with, by making it understandable and logical,I would like to thank the instructor. Sir, you have explained everything so well and clearly step by step. It has been very helpful

Simple Linear Regression with a Binary (or Nominal Categorical) Predictor - Simple Regression Analysis in Public Health
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