Answer:
To create a table for the case study with the 'person' column and information like name, age, gender, and annual income, you can follow this structure:
Person Name Age Gender Annual Income
1 John 30. Male 50000
2 Alice 25 Female 60000
3 Bob 35 Male 70000
... ... ... ... ...
To implement binary logistic regression using a single categorical predictor in this case, you would typically use the gender as the predictor variable to predict a binary outcome. This involves fitting a logistic regression model to predict the likelihood of a binary outcome based on the predictor variable (gender in this case).
Here are the general steps to implement binary logistic regression with a single categorical predictor:
Data Preparation: Ensure your data is clean and properly formatted.
Model Building: Fit a logistic regression model using a statistical software or programming language.
Model Evaluation: Evaluate the model's performance using metrics like accuracy, precision, recall, and F1 score.
Interpret Results: Interpret the coefficients of the logistic regression model to understand the impact of the predictor variable on the outcome.
By following these steps, you can successfully implement binary logistic regression using a single categorical predictor in the given case study.