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Statistics

Q. Explain the different design methods used in A/B Testing
Q. Explain the difference between Maximum Likelihood Estimate (MLE) and Maximum a Posteriori (MAP) Estimate
Q. What are the main components of a Bayesian Model?
Q. How does Bayesian Statistics differ from the Frequentist paradigm?
Q. What is Local Outlier Factor?
Q. What is Isolation Forest?
Q. What are some automatic outlier detection mechanisms?
Q. What are some options for dealing with outliers?
Q. What is an Outlier?
Q. What is Skewness and Kurtosis?
Q. How to choose between mean and median to summarize data?
Q. What is the difference between Mean, Median and Mode?
Q. What is a Confidence Interval?
Q. What is a p-value, and what is its significance?
Q. What is the difference between probability and likelihood?
Q. What is the Central Limit Theorem (CLT), and what are its implications for statistical inference?
Q. What are some desirable properties of estimators?
Q. What are the pros and cons of parametric vs. non-parametric models?
Q. What is the difference between parametric and non-parametric models?
Q. What is the relationship between independence and correlation?
Q. What is the difference between covariance and correlation?
Q. What is Chebyshev’s Theorem and its implications?
Q. What is the Empirical Rule?
Q. What is a Z Score?
Q. What does it mean if observations are iid, and why is this a desirable property?
Q. What is Kolmogorov–Smirnov statistic?
Q. What is the difference between a Probability Mass Function (PMF), Probability Density Function (PDF), and Cumulative Distribution Function (CDF)?
Q. What is a random variable?
Q. What is Bayes’ Rule?
Q. What is conditional probability?
Q. What does it mean for two events to be independent?
Q. What does it mean for two events to be mutually exclusive?
Q. What is a probability function, and what properties must it satisfy?
Q. What is the difference between a parameter and a statistic?

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Explore Questions by Topics

Computer Vision (1)
Data Preparation (35)
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- Sampling Techniques (5)
Deep Learning (52)
- DL Architectures (17)
  - Feedforward Network / MLP (2)
  - Sequence models (6)
  - Transformers (9)
- DL Basics (16)
- DL Training and Optimization (17)
Generative AI (2)
Machine Learning Basics (18)
Natural Language Processing (27)
- NLP Data Preparation (18)
Statistics (34)
Supervised Learning (115)
- Classification (70)
  - Classification Evaluations (9)
  - Ensemble Learning (24)
  - Logistic Regression (10)
  - Other Classification Models (9)
  - Support Vector Machine (9)
- Regression (41)
  - Generalized Linear Models (9)
  - Linear Regression (26)
  - Regularization (6)
Unsupervised Learning (55)
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  - Clustering Evaluations (6)
  - Distance Measures (9)
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  - K-Means Clustering (9)
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Other Questions in Statistics

What is CART?
What are the best ways to safeguard against overfitting a GBM?
How is Gradient Boosting different from Random Forest?
Distinguish between a Weak learner and a Strong Learner
What is Bagging? How do you perform bagging and what are its advantages?
Why is Random Forest a non-linear model? Why does it result in non-linear decision boundaries?

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