[Tutorialsplanet.NET] Udemy - Probability for Statistics and Data Science

•  4. Distributions/29. Practical Example Distributions.mp4  157.47 MB
•  3. Bayesian Inference/22. Practical Example Bayesian Inference.mp4  144.96 MB
•  2. Combinatorics/20. Practical Example Combinatorics.mp4  134.38 MB
•  5. Tie-ins to Other Fields/1. Tie-ins to Finance.mp4  98.83 MB
•  4. Distributions/3. What are the two main types of distributions based on the type of data we have.mp4  91.61 MB
•  1. Introduction to Probability/2. What is the probability formula.mp4  85.88 MB
•  4. Distributions/15. What is a Continuous Distribution.mp4  84.16 MB
•  5. Tie-ins to Other Fields/2. Tie-ins to Statistics.mp4  77.19 MB
•  1. Introduction to Probability/4. How to compute expected values.mp4  75.74 MB
•  4. Distributions/1. What is a probability distribution.mp4  73.36 MB
•  4. Distributions/11. What is the Binomial Distribution.mp4  68.89 MB
•  5. Tie-ins to Other Fields/3. Tie-ins to Data Science.mp4  63.46 MB
•  1. Introduction to Probability/6. What is a probability frequency distribution.mp4  61.61 MB
•  1. Introduction to Probability/8. What is a complement.mp4  59.11 MB
•  2. Combinatorics/11. What are combinations and how are they similar to variations.mp4  57.3 MB
•  3. Bayesian Inference/7. What is the union of sets A and B.mp4  57.21 MB
•  4. Distributions/13. What is the Poisson Distribution.mp4  55.8 MB
•  1. Introduction to Probability/1. What does the course cover.mp4  52.68 MB
•  3. Bayesian Inference/20. When do we use Bayes' Theorem in Real Life.mp4  50 MB
•  4. Distributions/27. What is the Logistic Distribution.mp4  49.98 MB
•  3. Bayesian Inference/18. How do we derive the Multiplication Rule formula.mp4  49.06 MB
•  4. Distributions/19. Standardizing a Normal Distribution.mp4  47.92 MB
•  3. Bayesian Inference/3. What are the different ways two events can interact with one another.mp4  47.44 MB
•  3. Bayesian Inference/13. What is the difference between P(AB) and P(BA).mp4  45.84 MB
•  3. Bayesian Inference/1. What is a set.mp4  45.52 MB
•  4. Distributions/17. What is a Normal Distribution.mp4  43.75 MB
•  2. Combinatorics/9. What if we couldn't use certain values more than once.mp4  43.08 MB
•  2. Combinatorics/3. When do we use Permutations.mp4  41.49 MB
•  2. Combinatorics/17. What is the chance of a single ticket winning the lottery.mp4  41.32 MB
•  2. Combinatorics/13. What is symmetry in Combinations.mp4  40.27 MB
•  4. Distributions/25. What is an Exponential Distribution.mp4  40.17 MB
•  2. Combinatorics/19. A Summary of Combinatorics.mp4  38.31 MB
•  2. Combinatorics/5. Solving Factorials.mp4  36.13 MB
•  3. Bayesian Inference/15. Conditional Probability in Real-Life.mp4  34.91 MB
•  3. Bayesian Inference/11. What does it mean to for two events to be dependent.mp4  34.78 MB
•  4. Distributions/9. What is the Bernoulli Distribution.mp4  34.15 MB
•  2. Combinatorics/7. Why can we use certain values more than once.mp4  33.97 MB
•  2. Combinatorics/15. How do we combine combinations of events with separate sample spaces.mp4  33.04 MB
•  3. Bayesian Inference/16. How do we apply the additive rule.mp4  26.95 MB
•  3. Bayesian Inference/5. What is the intersection of sets A and B.mp4  26.93 MB
•  4. Distributions/23. What is a Chi Squared Distribution.mp4  26.37 MB
•  3. Bayesian Inference/9. Are all complements mutually exclusive.mp4  25.4 MB
•  4. Distributions/7. What is the Discrete Uniform Distribution.mp4  24.4 MB
•  4. Distributions/5. Discrete Distributions and their characteristics..mp4  22.68 MB
•  4. Distributions/21. What is a Student's T Distribution.mp4  22 MB
•  2. Combinatorics/1. Why are combinatorics useful.mp4  16.17 MB
•  4. Distributions/29.3 FIFA19 (post).csv  8.65 MB
•  4. Distributions/29.4 FIFA19.csv  8.65 MB
•  3. Bayesian Inference/22.1 CDS_2017-2018 Hamilton.pdf  845.31 KB
•  4. Distributions/1.1 Course Notes - Probability Distributions.pdf  448.06 KB