Introduction to International Business Analytics-expert CHOOLS No Comment 04Sep Share Welcome to your Introduction to International Business Analytics-expert Which advanced statistical method is used to model complex, non-linear relationships between variables? A) Generalized Additive Models (GAM) B) Ordinary Least Squares (OLS) C) Logistic Regression D) Principal Component Analysis (PCA) What technique is commonly used to address high-dimensional data in business analytics? A) Regularization (L1 and L2) B) Cluster Analysis C) Time Series Decomposition D) Survival Analysis In international business analytics, which model is used for multi-class classification problems? A) Softmax Regression B) Naive Bayes C) Support Vector Machine (SVM) D) K-Nearest Neighbors (KNN) What is the primary purpose of 'differential privacy' in data analysis? A) To ensure individual data points cannot be identified B) To increase data accuracy C) To enhance data visualization D) To integrate data from multiple sources Which approach is used to analyze and optimize supply chain networks in international business analytics? A) Network Optimization B) Market Basket Analysis C) Customer Lifetime Value Analysis D) Time Series Forecasting What is 'feature engineering' crucial for in advanced machine learning models? A) Creating meaningful features from raw data to improve model performance B) Cleaning and preprocessing data C) Clustering data points D) Visualizing data Which algorithm is suitable for detecting anomalies in large datasets? A) Isolation Forest B) K-Means Clustering C) Principal Component Analysis (PCA) D) Naive Bayes What is the primary use of 'latent variable models' in international business analytics? A) To uncover hidden variables that explain observed data B) To classify data into categories C) To cluster similar data points D) To forecast future trends Which technique is used for dimensionality reduction that retains the maximum variance in the dataset? A) Principal Component Analysis (PCA) B) Linear Discriminant Analysis (LDA) C) t-Distributed Stochastic Neighbor Embedding (t-SNE) D) Factor Analysis Which advanced technique is used to handle missing data by creating multiple datasets with different imputations? A) Multiple Imputation by Chained Equations (MICE) B) Mean Imputation C) K-Nearest Neighbors Imputation D) Hot-Deck Imputation What is the main purpose of 'causal inference' in business analytics? A) To determine the cause-and-effect relationships between variables B) To classify data into categories C) To cluster similar data points D) To predict future trends What is the purpose of 'cross-validation' in model selection? A) To assess how the model generalizes to an independent dataset B) To improve the accuracy of predictions C) To select features for the model D) To clean and preprocess data Which technique is used to assess the stability and robustness of a predictive model? A) Sensitivity Analysis B) ROC Curve C) Precision-Recall Curve D) Feature Importance In international business analytics, which technique is used to handle large-scale, unstructured data? A) Hadoop Distributed File System (HDFS) B) SQL Databases C) Relational Databases D) Excel Spreadsheets What does 'ensemble learning' involve in machine learning? A) Combining multiple models to improve prediction performance B) Cleaning and preprocessing data C) Reducing the dimensionality of data D) Clustering similar data points Which method is used to validate the stability of model performance across different subsets of data? A) Bootstrap Aggregation (Bagging) B) Data Normalization C) Principal Component Analysis (PCA) D) Feature Scaling What is the purpose of 'conjoint analysis' in international business analytics? A) To understand customer preferences and value propositions B) To analyze time series data C) To cluster similar data points D) To handle missing data Which advanced technique is used for modeling hierarchical data structures? A) Hierarchical Linear Modeling (HLM) B) Logistic Regression C) Support Vector Machine (SVM) D) K-Means Clustering Which method is used for detecting multicollinearity in regression analysis? A) Variance Inflation Factor (VIF) B) Principal Component Analysis (PCA) C) K-Means Clustering D) t-Distributed Stochastic Neighbor Embedding (t-SNE) Which technique is used to optimize the parameters of machine learning models? A) Grid Search B) Data Imputation C) Data Normalization D) Feature Selection What is the primary goal of 'quantile regression' in business analytics? A) To model the conditional quantiles of the response variable B) To cluster similar data points C) To forecast future trends D) To handle missing data Time is Up! Previous Introduction to International Business Analytics-intermediate September 4, 2024 Next Software Testing September 14, 2024 You Might Also Like Hello world CHOOLS No Comment How to Disable Avast Antivirus CHOOLS No Comment AVG Review — Is the Absolutely free Version As effective as the Premium Version? CHOOLS No Comment Understanding the Limitations of Models of Managing CHOOLS No Comment Careers Similar To Teaching CHOOLS No Comment
