GigaCourse com Udemy Probability for Statistics and Data Science

/1. Introduction to Probability/

1. What does the course cover.mp4

1. What does the course cover.srt

2. What is the probability formula.mp4

2. What is the probability formula.srt

2.1 Section 1 Course Notes.pdf

3. What is the probability formula.html

4. How to compute expected values.mp4

4. How to compute expected values.srt

5. How to compute expected values.html

6. What is a probability frequency distribution.mp4

6. What is a probability frequency distribution.srt

7. What is a probability frequency distribution.html

8. What is a complement.mp4

8. What is a complement.srt

9. What is a complement.html

/2. Combinatorics/

1. Why are combinatorics useful.mp4

1. Why are combinatorics useful.srt

1.1 Section 2 Course Notes.pdf

10. Computing Variations without Repetition.html

11. What are combinations and how are they similar to variations.mp4

11. What are combinations and how are they similar to variations.srt

11.1 Combinations With Repetition.pdf

12. What are combinations and how are they similar to variations.html

13. What is symmetry in Combinations.mp4

13. What is symmetry in Combinations.srt

13.1 Symmetry Explained.pdf

14. What is symmetry in Combinations.html

15. How do we combine combinations of events with separate sample spaces.mp4

15. How do we combine combinations of events with separate sample spaces.srt

16. How do we combine combinations of events with separate sample spaces.html

17. What is the chance of a single ticket winning the lottery.mp4

17. What is the chance of a single ticket winning the lottery.srt

18. What is the chance of winning the lottery.html

19. A Summary of Combinatorics.mp4

19. A Summary of Combinatorics.srt

2. Why are combinatorics useful.html

20. Practical Example Combinatorics.mp4

20. Practical Example Combinatorics.srt

20.1 Additional Exercises Combinatorics.pdf

20.2 Additional Exercises Combinatorics Solutions.pdf

3. When do we use Permutations.mp4

3. When do we use Permutations.srt

4. When do we use Permutations.html

5. Solving Factorials.mp4

5. Solving Factorials.srt

6. Solving Factorials.html

7. Why can we use certain values more than once.mp4

7. Why can we use certain values more than once.srt

8. Why can we use certain values more than once.html

9. What if we couldn't use certain values more than once.mp4

9. What if we couldn't use certain values more than once.srt

/3. Bayesian Inference/

1. What is a set.mp4

1. What is a set.srt

1.1 Section 3 Course Notes.pdf

10. Are all complements mutually exclusive.html

11. What does it mean to for two events to be dependent.mp4

11. What does it mean to for two events to be dependent.srt

12. What does it mean to for two events to be dependent.html

13. What is the difference between P(AB) and P(BA).mp4

13. What is the difference between P(AB) and P(BA).srt

14. What is the difference between P(AB) and P(BA).html

15. Conditional Probability in Real-Life.mp4

15. Conditional Probability in Real-Life.srt

16. How do we apply the additive rule.mp4

16. How do we apply the additive rule.srt

17. How do we apply the additive rule.html

18. How do we derive the Multiplication Rule formula.mp4

18. How do we derive the Multiplication Rule formula.srt

19. How do we interpret the Multiplication Rule Formula.html

2. What is a set.html

20. When do we use Bayes' Theorem in Real Life.mp4

20. When do we use Bayes' Theorem in Real Life.srt

21. Bayes' Theorem.html

22. Practical Example Bayesian Inference.mp4

22. Practical Example Bayesian Inference.srt

22.1 Bayesian Homework .pdf

22.2 CDS_2017-2018 Hamilton.pdf

22.3 Bayesian Homework - Solutions.pdf

3. What are the different ways two events can interact with one another.mp4

3. What are the different ways two events can interact with one another.srt

4. What are the different ways two events can interact with one another.html

5. What is the intersection of sets A and B.mp4

5. What is the intersection of sets A and B.srt

6. What is the intersection of sets A and B.html

7. What is the union of sets A and B.mp4

7. What is the union of sets A and B.srt

8. What is the union of sets A and B.html

9. Are all complements mutually exclusive.mp4

9. Are all complements mutually exclusive.srt

/4. Distributions/

1. What is a probability distribution.mp4

1. What is a probability distribution.srt

1.1 Course Notes - Probability Distributions.pdf

10. What is the Bernoulli Distribution.html

11. What is the Binomial Distribution.mp4

11. What is the Binomial Distribution.srt

12. What is the Binomial Distribution.html

13. What is the Poisson Distribution.mp4

13. What is the Poisson Distribution.srt

13.1 Poisson - Expected Value and Variance.pdf

14. What is the Poisson Distribution.html

15. What is a Continuous Distribution.mp4

15. What is a Continuous Distribution.srt

15.1 Solving Integrals.pdf

16. What is a Continuous Distribution.html

17. What is a Normal Distribution.mp4

17. What is a Normal Distribution.srt

17.1 Normal Distribution - Expected Value and Variance.pdf

18. What is a Normal Distribution.html

19. Standardizing a Normal Distribution.mp4

19. Standardizing a Normal Distribution.srt

2. What is a probability distribution.html

20. How do we Standardize a Normal Distribution.html

21. What is a Student's T Distribution.mp4

21. What is a Student's T Distribution.srt

22. What is a Student's T Distribution.html

23. What is a Chi Squared Distribution.mp4

23. What is a Chi Squared Distribution.srt

24. What is a Chi-Squared Distribution.html

25. What is an Exponential Distribution.mp4

25. What is an Exponential Distribution.srt

26. What is an Exponential Distribution.html

27. What is the Logistic Distribution.mp4

27. What is the Logistic Distribution.srt

28. What is a Logistic Distribution.html

29. Practical Example Distributions.mp4

29. Practical Example Distributions.srt

29.1 Customers_Membership.xlsx

29.2 Daily Views (post).xlsx

29.3 FIFA19.csv

29.4 Customers_Membership (post).xlsx

29.5 Daily Views.xlsx

29.6 FIFA19 (post).csv

3. What are the two main types of distributions based on the type of data we have.mp4

3. What are the two main types of distributions based on the type of data we have.srt

4. What are the two main types of distributions based on the type of data we have.html

5. Discrete Distributions and their characteristics..mp4

5. Discrete Distributions and their characteristics..srt

6. Discrete Distributions and Their Characteristics..html

7. What is the Discrete Uniform Distribution.mp4

7. What is the Discrete Uniform Distribution.srt

8. What is the Discrete Uniform Distribution.html

9. What is the Bernoulli Distribution.mp4

9. What is the Bernoulli Distribution.srt

/5. Tie-ins to Other Fields/

1. Tie-ins to Finance.mp4

1. Tie-ins to Finance.srt

1.1 Probability in Finance Homework.pdf

1.2 Probability in Finance Solutions.pdf

2. Tie-ins to Statistics.mp4

2. Tie-ins to Statistics.srt

3. Tie-ins to Data Science.mp4

3. Tie-ins to Data Science.srt

/

Readme.txt

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