Model Evaluation and Validation

In this 10-minute Statistics Basics interview, you will be asked a series of verbal questions to demonstrate your understanding of statistical concepts and probability. You can expect to be asked to explain the difference between descriptive and inferential statistics, discuss probability distributions and their applications, and explore hypothesis testing, including concepts like null and alternative hypotheses, p-values, and significance levels. Additionally, you will be inquired about confidence intervals and how they are used in statistical analysis, as well as real-world applications of statistical methods in data analysis. Throughout the interview, you will be encouraged to explain your thought process and provide examples from your experience.

This interview evaluates your understanding of statistical hypothesis testing, including null and alternative hypotheses, p-values, significance levels, and common statistical tests.

This interview focuses on your approach to exploring and understanding datasets before formal modeling, including data visualization, summary statistics, and pattern identification.

This interview tests your ability to create, select, and transform features to improve machine learning model performance.

This interview focuses on techniques for handling missing data, outliers, and preparing datasets for analysis and modeling.