Complete Tutorial on Logistic Regression in One Video.

Introduction to the Case:
The tutorial covers a logistic regression case taught by Dr. U. Dinesh Kumar at IIM Bangalore. It involves Shubham Housing Finance, which provides loans to individuals in the unorganized sector lacking proper documentation.
Logistic Regression Application:
Logistic regression is used to predict loan approval (Y=1) or rejection (Y=0). The dependent variable is categorical, making logistic regression a suitable method. The main focus is on the loan-to-asset value (LTV) ratio and its impact on loan decisions.
Using Blue Sky Statistics:
The tutorial demonstrates the logistic regression process using Blue Sky Statistics software. Steps include loading data, selecting variables, running the model, and interpreting outputs like coefficients and probabilities.
Model Evaluation:
Evaluation metrics such as confusion matrix, specificity, sensitivity, and ROC curve are discussed. These metrics help in understanding model performance and determining the optimal cut-off point for loan approval decisions.
Optimal Cut-Off Point:
The tutorial emphasizes the importance of finding the best cut-off point using Uden's index and penalties for false positives and negatives. This helps in minimizing errors and making informed loan approval decisions.

[@jyotilaljani7499]

Excellent sir

[@KZZFOOTAGE]

Thank you for sharing Sir