School of Technology, Innovation and Research (TIR)

  SmartPLS   Statistical Research Software SmartPLS 4 is a powerful statistical software designed for structural equation modeling (SEM), combining ease of use with advanced analytical capabilities. It supports both Partial Least Squares SEM (PLS-SEM) and Covariance-Based SEM (CB-SEM), along with regression, factor analysis, and more. Key Features of SmartPLS 4 PLS-SEM + CB-SEM : Offers both variance-based and covariance-based SEM approaches. Regression & Factor Analysis : Beyond SEM, it supports traditional statistical techniques. User-Friendly Interface : Designed to simplify complex modeling tasks with intuitive workflows. Visualization Tools : Clear graphical outputs for path models and latent constructs. Structural Equation Modeling (SEM) is a statistical technique that combines factor analysis and regression to study complex relationships among variables, including both direct and indirect effects. It’s widely used in social sc...

  Logistic Regression Model for Bank loan Default Selection A logit model (or logistic regression model) is a statistical method used to predict the probability of a binary outcome (like yes/no, success/failure) based on one or more independent variables. It transforms a linear combination of predictors into probabilities between 0 and 1 using the logistic function. Example Imagine a bank wants to predict whether a loan applicant will default: Dependent variable: Default (1 = yes, 0 = no) Independent variables: Income, credit score, age The logit model estimates how these factors influence the probability of default. Let’s build a logit model example for predicting bank loan default using the three independent variables we mentioned: Income, Credit Score, and Age . Example: Bank Default Prediction Model Setup Dependent variable (Y): Default (1 = default, 0 = no default) Independent variables (X): (X_1): Income (in $10...