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    • Data Science Masterclass With R! 4 Projects+8 Case Studies

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    5. 10. Introduction To Statistics
    6. Files

    Files

      • DOCsDOCs
        • 21.1 Introduction-to-Statistics-codes-word-version.docx.docx21.1 Introduction-to-Statistics-codes-word-version.docx.docx
        • 21.2 Introduction-to-Statistics-codes-word-version.docx.docx21.2 Introduction-to-Statistics-codes-word-version.docx.docx
      • HTMLHTML
        • 2. Introduction To Statistic - Part 1 STUDY NOTE.html2. Introduction To Statistic - Part 1 STUDY NOTE.html
        • 4. Introduction To Statistic - Part 2 STUDY NOTE.html4. Introduction To Statistic - Part 2 STUDY NOTE.html
        • 6. Introduction To Statistic - Part 3 STUDY NOTE.html6. Introduction To Statistic - Part 3 STUDY NOTE.html
        • 8. Part 4 Introduction To Statistic STUDY NOTE.html8. Part 4 Introduction To Statistic STUDY NOTE.html
        • 10. Introduction To Statistic - Part 5 STUDY NOTE.html10. Introduction To Statistic - Part 5 STUDY NOTE.html
        • 13. Introduction To Statistic - Part 7 STUDY NOTE.html13. Introduction To Statistic - Part 7 STUDY NOTE.html
        • 15. Introduction To Statistic - Part 8 STUDY NOTE.html15. Introduction To Statistic - Part 8 STUDY NOTE.html
        • 17. Introduction To Statistic - Part 9 STUDY NOTE.html17. Introduction To Statistic - Part 9 STUDY NOTE.html
        • 19. Introduction To Statistic - Part 10 STUDY NOTE.html19. Introduction To Statistic - Part 10 STUDY NOTE.html
        • 21. Introduction To Statistics - All Codes.html21. Introduction To Statistics - All Codes.html
      • PDFsPDFs
        • 21.1 Intro-To-Statistic.pdf.pdf21.1 Intro-To-Statistic.pdf.pdf
        • 21.2 Intro-To-Statistic.pdf.pdf21.2 Intro-To-Statistic.pdf.pdf

    ◄ 20. Intro To Stat - Part 11
    1. Hypothesys Testing - Part 1 ►
    • R master
    • 1. Meet Your Instructor
    • 2. INTRODUCTION TO DATA SCIENCE
    • 3. Course Curriculum Overview
    • 4. INTRODUCTION TO R
    • 5. R Programming
    • 6. R Data Structure
    • 7. Import and Export in R
    • 8. Data Manipulation
    • 9. Data Visualization
    • 10. Introduction To Statistics
    • 11. HYPOTHESIS Testing -1
    • 12. Hypothesis Testing in Practice
    • 13. Machine Learning Toolbox
    • 14. Business Use Case Understaing
    • Topic 14
    • 15. Data Pre-Processing
    • 16. SUPERVISED LEARNING REGRESSION
    • 17. Classification Overview
    • 17. Logistic Regression
    • 18. K-NN
    • 18. Logistic Regression
    • 19. K-NN
    • 19. SVM
    • 20. Naive Bayes
    • 20. SVM
    • 21. Decision Tree
    • 21. Naive Bayes
    • 22. Decision Tree
    • 22. Random Forest
    • 23. Capstone Project - Titanic Survival
    • 23. Random Forest
    • 23. Capstone Project - Titanic Survival
    • 24. Capstone Project - Titanic Survival
    • 24. K-Mean Clustering
    • 25. Hierarchical Clustering
    • 25. K-Mean Clustering
    • 26. DBScan Clustering
    • 26. Hierarchical Clustering
    • 27. DBScan Clustering
    • 27. Principal Component Analysis (PCA)
    • 28. Association Rule Mining
    • 29. Association Rule Mining
    • 29. Capstone Project - Big Mart Sell
    • 30. Capstone Project - Big Mart Sell
    • 30. Model Deployment
    • 31. Bonus Section - $997 Value Inside
    • 31. Model Deployment
    • 32. Bonus Section - $997 Value Inside
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