udemy-probability-for-statistics-and-data-science

磁力链接/BT种子名称

udemy-probability-for-statistics-and-data-science

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种子哈希：37751c62bc06fc3b9294ff8e2ee03f855677aba2
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收录时间：2022-01-22
最近下载：2025-09-13

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文件列表

  • 4. Distributions/29. Practical Example Distributions.mp4 165.1 MB
  • 3. Bayesian Inference/22. Practical Example Bayesian Inference.mp4 152.0 MB
  • 2. Combinatorics/20. Practical Example Combinatorics.mp4 140.9 MB
  • 5. Tie-ins to Other Fields/1. Tie-ins to Finance.mp4 103.6 MB
  • 4. Distributions/3. What are the two main types of distributions based on the type of data we have.mp4 96.1 MB
  • 1. Introduction to Probability/2. What is the probability formula.mp4 90.0 MB
  • 4. Distributions/15. What is a Continuous Distribution.mp4 88.2 MB
  • 5. Tie-ins to Other Fields/2. Tie-ins to Statistics.mp4 80.9 MB
  • 1. Introduction to Probability/4. How to compute expected values.mp4 79.4 MB
  • 4. Distributions/1. What is a probability distribution.mp4 76.9 MB
  • 4. Distributions/11. What is the Binomial Distribution.mp4 72.2 MB
  • 5. Tie-ins to Other Fields/3. Tie-ins to Data Science.mp4 66.5 MB
  • 1. Introduction to Probability/6. What is a probability frequency distribution.mp4 64.6 MB
  • 1. Introduction to Probability/8. What is a complement.mp4 62.0 MB
  • 2. Combinatorics/11. What are combinations and how are they similar to variations.mp4 60.1 MB
  • 3. Bayesian Inference/7. What is the union of sets A and B.mp4 60.0 MB
  • 4. Distributions/13. What is the Poisson Distribution.mp4 58.5 MB
  • 1. Introduction to Probability/1. What does the course cover.mp4 55.2 MB
  • 3. Bayesian Inference/20. When do we use Bayes' Theorem in Real Life.mp4 52.4 MB
  • 4. Distributions/27. What is the Logistic Distribution.mp4 52.4 MB
  • 3. Bayesian Inference/18. How do we derive the Multiplication Rule formula.mp4 51.4 MB
  • 4. Distributions/19. Standardizing a Normal Distribution.mp4 50.2 MB
  • 3. Bayesian Inference/3. What are the different ways two events can interact with one another.mp4 49.7 MB
  • 3. Bayesian Inference/13. What is the difference between P(AB) and P(BA).mp4 48.1 MB
  • 3. Bayesian Inference/1. What is a set.mp4 47.7 MB
  • 4. Distributions/17. What is a Normal Distribution.mp4 45.9 MB
  • 2. Combinatorics/9. What if we couldn't use certain values more than once.mp4 45.2 MB
  • 2. Combinatorics/3. When do we use Permutations.mp4 43.5 MB
  • 2. Combinatorics/17. What is the chance of a single ticket winning the lottery.mp4 43.3 MB
  • 2. Combinatorics/13. What is symmetry in Combinations.mp4 42.2 MB
  • 4. Distributions/25. What is an Exponential Distribution.mp4 42.1 MB
  • 2. Combinatorics/19. A Summary of Combinatorics.mp4 40.2 MB
  • 2. Combinatorics/5. Solving Factorials.mp4 37.9 MB
  • 3. Bayesian Inference/15. Conditional Probability in Real-Life.mp4 36.6 MB
  • 3. Bayesian Inference/11. What does it mean to for two events to be dependent.mp4 36.5 MB
  • 4. Distributions/9. What is the Bernoulli Distribution.mp4 35.8 MB
  • 2. Combinatorics/7. Why can we use certain values more than once.mp4 35.6 MB
  • 2. Combinatorics/15. How do we combine combinations of events with separate sample spaces.mp4 34.6 MB
  • 3. Bayesian Inference/16. How do we apply the additive rule.mp4 28.3 MB
  • 3. Bayesian Inference/5. What is the intersection of sets A and B.mp4 28.2 MB
  • 4. Distributions/23. What is a Chi Squared Distribution.mp4 27.6 MB
  • 3. Bayesian Inference/9. Are all complements mutually exclusive.mp4 26.6 MB
  • 4. Distributions/7. What is the Discrete Uniform Distribution.mp4 25.6 MB
  • 4. Distributions/5. Discrete Distributions and their characteristics..mp4 23.8 MB
  • 4. Distributions/21. What is a Student's T Distribution.mp4 23.1 MB
  • 2. Combinatorics/1. Why are combinatorics useful.mp4 17.0 MB
  • 3. Bayesian Inference/22.1 CDS_2017-2018 Hamilton_jp2.zip 13.8 MB
  • 4. Distributions/29.3 FIFA19 (post).csv 9.1 MB
  • 4. Distributions/29.4 FIFA19.csv 9.1 MB
  • 4. Distributions/1.1 Course Notes - Probability Distributions_jp2.zip 8.2 MB
  • 1. Introduction to Probability/2.1 Section 1 Course Notes_jp2.zip 4.1 MB
  • 4. Distributions/15.1 Solving Integrals_jp2.zip 3.0 MB
  • 3. Bayesian Inference/1.1 Section 3 Course Notes_jp2.zip 2.5 MB
  • 2. Combinatorics/20.2 Additional Exercises Combinatorics Solutions_jp2.zip 2.5 MB
  • 2. Combinatorics/11.1 Combinations With Repetition_jp2.zip 2.3 MB
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  • 2. Combinatorics/1.1 Section 2 Course Notes_jp2.zip 1.4 MB
  • 4. Distributions/17.1 Normal Distribution - Expected Value and Variance_jp2.zip 1.3 MB
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  • 3. Bayesian Inference/22.1 CDS_2017-2018 Hamilton_abbyy.gz 1.3 MB
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  • 5. Tie-ins to Other Fields/1.2 Probability in Finance Solutions_jp2.zip 1.1 MB
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  • 2. Combinatorics/20.1 Additional Exercises Combinatorics_jp2.zip 808.3 kB
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  • 4. Distributions/13.1 Poisson - Expected Value and Variance_jp2.zip 507.9 kB
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  • 4. Distributions/1.1 Course Notes - Probability Distributions.pdf 458.8 kB
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  • 3. Bayesian Inference/1.1 Section 3 Course Notes.pdf 395.3 kB
  • 5. Tie-ins to Other Fields/1.1 Probability in Finance Homework_jp2.zip 390.6 kB
  • 1. Introduction to Probability/2.1 Section 1 Course Notes.pdf 380.0 kB
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