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Udemy - Statistics for Data Science - A Comprehensive Journey

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Udemy - Statistics for Data Science - A Comprehensive Journey (Size: 1.4 GB)
  Bonus Resources.txt 102.4 B
  Get Bonus Downloads Here.url 204.8 B
  ~Get Your Files Here !
  1 - Introduction to the course
  1. Agenda.mp4 9 MB
  2 - Introduction to Statistics
  2. Sample and Population.mp4 6.8 MB
  3 - Probability
  10. Probability Event Types Mutual Exclusive and Independent.mp4 22.7 MB
  11. Probability Types Marginal Joint and Conditional.mp4 24.8 MB
  12. Marginal Joint and Conditional Probability Solved Examples.mp4 35.7 MB
  13. Bay’s Theorem.mp4 40.8 MB
  14. Bays Theorem Solved Problem.mp4 25.7 MB
  15. Bays Theorem Solved Problem.mp4 25.9 MB
  16. Bays Theorem Solved Problem.mp4 33.6 MB
  4 - Probability Distributions
  17. Random Variable.mp4 32.6 MB
  18. Discrete Random Variable Solved Example.mp4 26.9 MB
  19. Continuous Random Variable.mp4 66.2 MB
  20. Continuous Random Variable Solved Example.mp4 25.9 MB
  21. Probability Distributions.mp4 58.7 MB
  22. Binomial Distribution.mp4 52 MB
  23. Binomial Distribution Solved Problem.mp4 32.3 MB
  24. Uniform Distribution.mp4 19.7 MB
  25. Uniform Distribution Solved Example.mp4 18.9 MB
  26. Normal Distribution.mp4 10.2 MB
  27. Why Normal Distribution Understanding is important in Data Science.html 3.7 KB
  28. Properties of Normal Distribution and Examples.mp4 71.1 MB
  29. Standard Normal Distribution with example.mp4 44 MB
  5 - Hypothesis Testing
  30. Understanding What is a Hypothesis Testing is all about.mp4 49.5 MB
  31. Terms in Hypothesis Testing.mp4 8.1 MB
  32. Steps for Hypothesis Testing.mp4 4 MB
  33. Understanding Hypothesis Testing While Solving a Problem.mp4 56.2 MB
  34. Summarize the Hypothesis Testing.mp4 6.3 MB
  6 - ANOVA
  35. Introduction.mp4 12.8 MB
  36. What is Variance.mp4 47.9 MB
  37. Meaning of Statistically Significant.mp4 47.2 MB
  38. t tests using an example.mp4 106.7 MB
  39. Perform t test on sample data using excel.mp4 122.8 MB
  40. ANOVA.mp4 65.5 MB
  41. One Way ANOVA Example.mp4 120.5 MB
  8. What is Probability.mp4 20.8 MB
  9. Probability Solved Examples.mp4 15.1 MB
  3. Sampling Techniques.mp4 12.4 MB
  4. Descriptive Statistics.mp4 5.1 MB
  5. Descriptive Statistical Measures Computation.mp4 26.4 MB
  6. Data Distribution.mp4 11.3 MB
  7. Descriptive Statistics Real Time Example Water Quality pH Parameter.mp4 16.4 MB

Description


Statistics for Data Science: A Comprehensive Journey

https://WebToolTip.com

Published 1/2026
MP4 | Video: h264, 1920x1080 | Audio: AAC, 44.1 KHz, 2 Ch
Language: English | Duration: 4h 25m | Size: 1.4 GB

Building the Foundation of Statistical Knowledge for Data-Driven Insights

What you'll learn
Understand key statistical concepts like probability, distributions, and hypothesis testing for effective data-driven decisions.
Apply descriptive and inferential statistics to summarize data, draw conclusions, and make predictions.
Use statistical models like regression to analyze data, identifying patterns, relationships, and trends.
Evaluate data quality and apply statistical reasoning to solve data science problems and make informed decisions.

Requirements
Basic Mathematics - Familiarity with high school-level math, including algebra and basic arithmetic operations.
Foundational Data Concepts - Understanding of data types (e.g., categorical, numerical) and basic data handling in spreadsheets or simple programming environments.
Introductory Programming Knowledge - Basic experience in Python or R is helpful, as some examples and exercises may involve code.
Logical Thinking - Ability to analyze problems and approach them systematically, which is essential for statistical reasoning.

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