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Statistics Using Python | Statistics Python Tutorial | Python Certification Training | Edureka

** Python Certification Training: https://www.edureka.co/python ** <br>This Edureka PPT on Python Tutorial covers all the basic knowledge of statistics and probability for Python. <br><br>Why Python for Statistics? <br>What is Probability? <br>Data and Distribution <br>Revisiting the Normal <br>Poker Prediction Use-Case <br><br>Check out our Python Tutorial Playlist: https://goo.gl/WsBpKe <br>Follow us to never miss an update in the future. <br><br>Instagram: https://www.instagram.com/edureka_learning/ <br>Facebook: https://www.facebook.com/edurekaIN/ <br>Twitter: https://twitter.com/edurekain <br>LinkedIn: https://www.linkedin.com/company/edureka

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Statistics Using Python | Statistics Python Tutorial | Python Certification Training | Edureka

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  1. Agenda Python Certification Training https://www.edureka.co/python

  2. Agenda 01 Introduction Introduction to Statistics And Probability 02 Getting Started Getting Started With Python for Probability 03 Concepts Overview of the simple concepts that’s involved 04 Use Case A practical Python use-case to understand Python faster! Python Certification Training https://www.edureka.co/python

  3. Why Python For Statistics? Python Certification Training https://www.edureka.co/python

  4. Why Python For Statistics? R is a language dedicated for statistics! Then why Python? Building complex analysis pipelines that mix statistics with Image Analysis, Text Mining etc.. Here, the richness of Python is an invaluable asset! Python Certification Training https://www.edureka.co/python

  5. What is Probability? Python Certification Training https://www.edureka.co/python

  6. What is Probability? What is the chance of an event happening? How do you answer this? We need to consider all the other events that can occur before coming to a conclusion! Python Certification Training https://www.edureka.co/python

  7. The Coin Toss What are the outcomes for a coin toss? Flipping a heads Flipping a tails Any other outcome? NO! We call this the Sample Space! Python Certification Training https://www.edureka.co/python

  8. The Coin Toss What are the outcomes for a coin toss? A 100 Heads and 10 Tails, is this fair? Yes, the outcome here is to gather data, use statistics to make predictions and compare! Python Certification Training https://www.edureka.co/python

  9. The Coin Toss – Data Generation Python Certification Training https://www.edureka.co/python

  10. Too early for code? Python Certification Training https://www.edureka.co/python

  11. The Coin Toss – Code import random def coin_trial(): heads = 0 for i in range(100): if random.random() <= 0.5: heads +=1 return heads simulate(10) >> 5.4 simulate(100) >>> 4.83 simulate(1000) >>> 5.055 def simulate(n): trials = [] for i in range(n): trials.append(coin_trial()) return(sum(trials)/n) simulate(1000000) >>> 4.999781 Python Certification Training https://www.edureka.co/python

  12. The Coin Toss – The Theory Given enough data, statistics enables us to calculate probabilities using real-world observations Python Certification Training https://www.edureka.co/python

  13. The Coin Toss – Python What are the chances of someone developing a disease over time? What is probability that a critical car component will fail when you are driving? Pythonmaking our lives simpler with this! Python Certification Training https://www.edureka.co/python

  14. Data And Distribution Python Certification Training https://www.edureka.co/python

  15. Data And Distribution Let’s tackle “Which wine is better than average” You need to know the nature of the data! Normal Distribution Normal distribution refers to a particularly important phenomenon in the realm of probability and statistics. Python Certification Training https://www.edureka.co/python

  16. Data And Distribution The high point in a normal distribution represents the event with the highest probability of occurring! Python Certification Training https://www.edureka.co/python

  17. Revisiting The Normal Python Certification Training https://www.edureka.co/python

  18. Revisiting The Normal Two major factors Central Limit Theorem Three Sigma Rule Central Limit Theorem dictates that thedistributionof theestimateswill look like a normal distribution. The Three Sigma rule dictates thatgiven a normal distribution, 68% of your observations will fall between one standard deviation of the mean. 95% will fall within two, and 99.7% will fall within three. Learning Python Python Certification Training https://www.edureka.co/python

  19. Z-Score Learning Python Python Certification Training https://www.edureka.co/python

  20. Use-Case: Poker Probability Python Certification Training https://www.edureka.co/python

  21. Use-Case: Poker Prediction Can we predict the outcome of probability of occurrence of a poker hand? Python Certification Training https://www.edureka.co/python

  22. Use-Case: Poker Prediction Let’s look at the basics 52 cards in a standard deck! 4 of each shape For an Ace -P(A) = 4/52 Python Certification Training https://www.edureka.co/python

  23. Use-Case: Poker Prediction Poker Without Python Poker With Python Texas Hold’em Pre-Flop: Each player is dealt two cards, known as "hole cards" Flop: Three community cards are dealt Turn: One community card is dealt River: Final community card is dealt Python Certification Training https://www.edureka.co/python

  24. Use-Case: Poker Prediction Dependent Events: Flush Draw Your Hand Community Cards Python Certification Training https://www.edureka.co/python

  25. Use-Case: Poker Prediction Dependent Events: Open-Ended Straight Draw Your Hand Community Cards Python Certification Training https://www.edureka.co/python

  26. Use-Case: Poker Prediction Involve Opponents now! Your Hand Opponents Bet =$20 Total Pot =$60 Opponent’s Hand Community Cards Python Certification Training https://www.edureka.co/python

  27. Conclusion Python Certification Training https://www.edureka.co/python

  28. Conclusion Python Certification Training https://www.edureka.co/python

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