[FreeTutorials.Us] [UDEMY] Statistics for Data Science and Business Analysis [FTU]


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Creat Time:   2024-05-21
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Last Active:   2024-11-12
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Tags:    FreeTutorials Us UDEMY Statistics for Data Science and Business Analysis FTU
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File List

  1. 5. Practical example descriptive statistics/1. Practical example.mp4 223.04 MB
  2. 17. Practical example regression analysis/1. Practical example regression analysis.mp4 187.37 MB
  3. 9. Practical example inferential statistics/1. Practical example inferential statistics.mp4 105.05 MB
  4. 10. Hypothesis testing Introduction/1. The null and the alternative hypothesis.mp4 94.36 MB
  5. 10. Hypothesis testing Introduction/4. Establishing a rejection region and a significance level.mp4 84.52 MB
  6. 7. Estimators and estimates/5. Calculating confidence intervals within a population with a known variance.mp4 80.09 MB
  7. 8. Confidence intervals advanced topics/1. Calculating confidence intervals for two means with dependent samples.mp4 72.19 MB
  8. 12. Practical example hypothesis testing/1. Practical example hypothesis testing.mp4 71.04 MB
  9. 6. Distributions/9. Understanding the central limit theorem.mp4 64.39 MB
  10. 6. Distributions/2. What is a distribution.mp4 63.08 MB
  11. 7. Estimators and estimates/12. What is a margin of error and why is it important in Statistics.mp4 60.61 MB
  12. 16. Dealing with categorical data/1. Dummy variables.mp4 58.62 MB
  13. 7. Estimators and estimates/7. Confidence interval clarifications.mp4 58.48 MB
  14. 11. Hypothesis testing Let's start testing!/3. What is the p-value and why is it one of the most useful tools for statisticians.mp4 57.21 MB
  15. 3. The fundamentals of descriptive statistics/3. Levels of measurement.mp4 55.67 MB
  16. 11. Hypothesis testing Let's start testing!/1. Test for the mean. Population variance known.mp4 55.59 MB
  17. 13. The fundamentals of regression analysis/5. The linear regression model made easy.mp4 52.21 MB
  18. 4. Measures of central tendency, asymmetry, and variability/6. Measuring how data is spread out calculating variance.mp4 52.16 MB
  19. 11. Hypothesis testing Let's start testing!/7. Test for the mean. Dependent samples.mp4 51.65 MB
  20. 7. Estimators and estimates/3. Confidence intervals - an invaluable tool for decision making.mp4 51.13 MB
  21. 6. Distributions/4. The Normal distribution.mp4 51.06 MB
  22. 7. Estimators and estimates/1. Working with estimators and estimates.mp4 48.97 MB
  23. 13. The fundamentals of regression analysis/11. A practical example - Reinforced learning.mp4 46.97 MB
  24. 4. Measures of central tendency, asymmetry, and variability/8. Standard deviation and coefficient of variation.mp4 46.29 MB
  25. 10. Hypothesis testing Introduction/6. Type I error vs Type II error.mp4 44.99 MB
  26. 14. Subtleties of regression analysis/12. The adjusted R-squared.mp4 44.75 MB
  27. 4. Measures of central tendency, asymmetry, and variability/1. The main measures of central tendency mean, median and mode.mp4 43.91 MB
  28. 14. Subtleties of regression analysis/1. Decomposing the linear regression model - understanding its nuts and bolts.mp4 43.22 MB
  29. 11. Hypothesis testing Let's start testing!/5. Test for the mean. Population variance unknown.mp4 41.21 MB
  30. 15. Assumptions for linear regression analysis/7. A3. Normality and homoscedasticity.mp4 40.92 MB
  31. 3. The fundamentals of descriptive statistics/14. Cross tables and scatter plots.mp4 40.76 MB
  32. 1. Introduction/1. What does the course cover.mp4 39.67 MB
  33. 3. The fundamentals of descriptive statistics/5. Categorical variables. Visualization techniques for categorical variables.mp4 39.40 MB
  34. 2. Sample or population data/1. Understanding the difference between a population and a sample.mp4 37.80 MB
  35. 14. Subtleties of regression analysis/7. Studying regression tables.mp4 37.67 MB
  36. 14. Subtleties of regression analysis/3. What is R-squared and how does it help us.mp4 37.32 MB
  37. 11. Hypothesis testing Let's start testing!/11. Test for the mean. Independent samples (Part 2).mp4 37.25 MB
  38. 7. Estimators and estimates/8. Student's T distribution.mp4 36.25 MB
  39. 3. The fundamentals of descriptive statistics/1. The various types of data we can work with.mp4 35.84 MB
  40. 15. Assumptions for linear regression analysis/5. A2. No endogeneity.mp4 33.22 MB
  41. 7. Estimators and estimates/10. Calculating confidence intervals within a population with an unknown variance.mp4 32.96 MB
  42. 11. Hypothesis testing Let's start testing!/9. Test for the mean. Independent samples (Part 1).mp4 30.68 MB
  43. 4. Measures of central tendency, asymmetry, and variability/13. The correlation coefficient.mp4 30.10 MB
  44. 8. Confidence intervals advanced topics/3. Calculating confidence intervals for two means with independent samples (part 1).mp4 29.45 MB
  45. 4. Measures of central tendency, asymmetry, and variability/11. Calculating and understanding covariance.mp4 28.12 MB
  46. 8. Confidence intervals advanced topics/5. Calculating confidence intervals for two means with independent samples (part 2).mp4 27.45 MB
  47. 15. Assumptions for linear regression analysis/11. A5. No multicollinearity.mp4 27.21 MB
  48. 15. Assumptions for linear regression analysis/9. A4. No autocorrelation.mp4 26.50 MB
  49. 3. The fundamentals of descriptive statistics/8. Numerical variables. Using a frequency distribution table.mp4 26.47 MB
  50. 13. The fundamentals of regression analysis/3. Correlation and causation.mp4 26.19 MB

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