FreeTutorials Us UDEMY Statistics for Data Science and Business Analysis FTU

1. 1. Introduction/1. What does the course cover.mp438.74MB
2. 10. Hypothesis testing Introduction/1. The null and the alternative hypothesis.mp492.15MB
3. 10. Hypothesis testing Introduction/4. Establishing a rejection region and a significance level.mp482.53MB
4. 10. Hypothesis testing Introduction/6. Type I error vs Type II error.mp443.93MB
5. 11. Hypothesis testing Let's start testing!/1. Test for the mean. Population variance known.mp454.29MB
6. 11. Hypothesis testing Let's start testing!/11. Test for the mean. Independent samples (Part 2).mp436.38MB
7. 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.mp455.87MB
8. 11. Hypothesis testing Let's start testing!/5. Test for the mean. Population variance unknown.mp440.25MB
9. 11. Hypothesis testing Let's start testing!/7. Test for the mean. Dependent samples.mp450.44MB
10. 11. Hypothesis testing Let's start testing!/9. Test for the mean. Independent samples (Part 1).mp429.96MB
11. 12. Practical example hypothesis testing/1. Practical example hypothesis testing.mp469.38MB
12. 13. The fundamentals of regression analysis/1. Introduction to regression analysis.mp419.4MB
13. 13. The fundamentals of regression analysis/11. A practical example - Reinforced learning.mp445.87MB
14. 13. The fundamentals of regression analysis/3. Correlation and causation.mp425.57MB
15. 13. The fundamentals of regression analysis/5. The linear regression model made easy.mp450.98MB
16. 13. The fundamentals of regression analysis/7. What is the difference between correlation and regression.mp412.72MB
17. 13. The fundamentals of regression analysis/9. A geometrical representation of the linear regression model.mp44.91MB
18. 14. Subtleties of regression analysis/1. Decomposing the linear regression model - understanding its nuts and bolts.mp442.21MB
19. 14. Subtleties of regression analysis/10. The multiple linear regression model.mp419.1MB
20. 14. Subtleties of regression analysis/12. The adjusted R-squared.mp443.7MB
21. 14. Subtleties of regression analysis/14. What does the F-statistic show us and why do we need to understand it.mp413.9MB
22. 14. Subtleties of regression analysis/3. What is R-squared and how does it help us.mp436.44MB
23. 14. Subtleties of regression analysis/5. The ordinary least squares setting and its practical applications.mp420.05MB
24. 14. Subtleties of regression analysis/7. Studying regression tables.mp436.78MB
25. 15. Assumptions for linear regression analysis/1. OLS assumptions.mp419.38MB
26. 15. Assumptions for linear regression analysis/11. A5. No multicollinearity.mp426.58MB
27. 15. Assumptions for linear regression analysis/3. A1. Linearity.mp412.06MB
28. 15. Assumptions for linear regression analysis/5. A2. No endogeneity.mp432.44MB
29. 15. Assumptions for linear regression analysis/7. A3. Normality and homoscedasticity.mp439.96MB
30. 15. Assumptions for linear regression analysis/9. A4. No autocorrelation.mp425.88MB
31. 16. Dealing with categorical data/1. Dummy variables.mp457.24MB
32. 17. Practical example regression analysis/1. Practical example regression analysis.mp4182.98MB
33. 2. Sample or population data/1. Understanding the difference between a population and a sample.mp436.92MB
34. 3. The fundamentals of descriptive statistics/1. The various types of data we can work with.mp435.01MB
35. 3. The fundamentals of descriptive statistics/11. Histogram charts.mp413.79MB
36. 3. The fundamentals of descriptive statistics/14. Cross tables and scatter plots.mp439.8MB
37. 3. The fundamentals of descriptive statistics/3. Levels of measurement.mp454.37MB
38. 3. The fundamentals of descriptive statistics/5. Categorical variables. Visualization techniques for categorical variables.mp438.47MB
39. 3. The fundamentals of descriptive statistics/8. Numerical variables. Using a frequency distribution table.mp425.85MB
40. 4. Measures of central tendency, asymmetry, and variability/1. The main measures of central tendency mean, median and mode.mp442.88MB
41. 4. Measures of central tendency, asymmetry, and variability/11. Calculating and understanding covariance.mp427.47MB
42. 4. Measures of central tendency, asymmetry, and variability/13. The correlation coefficient.mp429.4MB
43. 4. Measures of central tendency, asymmetry, and variability/3. Measuring skewness.mp419.41MB
44. 4. Measures of central tendency, asymmetry, and variability/6. Measuring how data is spread out calculating variance.mp450.93MB
45. 4. Measures of central tendency, asymmetry, and variability/8. Standard deviation and coefficient of variation.mp445.2MB
46. 5. Practical example descriptive statistics/1. Practical example.mp4217.81MB
47. 6. Distributions/1. Introduction to inferential statistics.mp415.47MB
48. 6. Distributions/11. Standard error.mp422.77MB
49. 6. Distributions/2. What is a distribution.mp461.61MB
50. 6. Distributions/4. The Normal distribution.mp449.86MB
51. 6. Distributions/6. The standard normal distribution.mp422.5MB
52. 6. Distributions/9. Understanding the central limit theorem.mp462.89MB
53. 7. Estimators and estimates/1. Working with estimators and estimates.mp447.83MB
54. 7. Estimators and estimates/10. Calculating confidence intervals within a population with an unknown variance.mp432.19MB
55. 7. Estimators and estimates/12. What is a margin of error and why is it important in Statistics.mp459.19MB
56. 7. Estimators and estimates/3. Confidence intervals - an invaluable tool for decision making.mp449.93MB
57. 7. Estimators and estimates/5. Calculating confidence intervals within a population with a known variance.mp478.21MB
58. 7. Estimators and estimates/7. Confidence interval clarifications.mp457.11MB
59. 7. Estimators and estimates/8. Student's T distribution.mp435.4MB
60. 8. Confidence intervals advanced topics/1. Calculating confidence intervals for two means with dependent samples.mp470.49MB
61. 8. Confidence intervals advanced topics/3. Calculating confidence intervals for two means with independent samples (part 1).mp428.76MB
62. 8. Confidence intervals advanced topics/5. Calculating confidence intervals for two means with independent samples (part 2).mp426.81MB
63. 8. Confidence intervals advanced topics/7. Calculating confidence intervals for two means with independent samples (part 3).mp419.89MB
64. 9. Practical example inferential statistics/1. Practical example inferential statistics.mp4102.59MB