Udemy - Statistics for Data Science and Business Analysis [GC]

Files:

• 1. What does the course cover.mp4 (68.6 MB)
• 1. What does the course cover.srt (5.6 KB)
• 1.1 Statistics Glossary.xlsx (20.3 KB)
• 2. Download all resources.html (0.7 KB)

• 1. The null and the alternative hypothesis.mp4 (92.2 MB)
• 1. The null and the alternative hypothesis.srt (7.0 KB)
• 1.1 Course notes_hypothesis_testing.pdf (656.4 KB)
• 2. Further reading on null and alternative hypotheses.html (2.3 KB)
• 3. Null vs alternative.html (0.2 KB)
• 4. Establishing a rejection region and a significance level.mp4 (82.5 MB)
• 4. Establishing a rejection region and a significance level.srt (8.7 KB)
• 4.1 Course notes_hypothesis_testing.pdf (656.4 KB)
• 5. Rejection region and significance level.html (0.2 KB)
• 6. Type I error vs Type II error.mp4 (43.9 MB)
• 6. Type I error vs Type II error.srt (5.4 KB)
• 7. Type I error vs type II error.html (0.2 KB)

• 1. Test for the mean. Population variance known.mp4 (54.3 MB)
• 1. Test for the mean. Population variance known.srt (7.5 KB)
• 1.1 4.4. Test for the mean. Population variance known_lesson.xlsx (11.0 KB)
• 10. Test for the mean. Independent samples (Part 1).html (0.1 KB)
• 10.1 4.8.Test-for-the-mean.Independent-samples-Part-1-exercise-solution.xlsx (11.3 KB)
• 10.2 4.8.Test-for-the-mean.Independent-samples-Part-1-exercise.xlsx (10.8 KB)
• 11. Test for the mean. Independent samples (Part 2).mp4 (36.4 MB)
• 11. Test for the mean. Independent samples (Part 2).srt (5.1 KB)
• 11.1 4.9. Test for the mean. Independent samples (Part 2)_lesson.xlsx (9.3 KB)
• 12. Test for the mean. Independent samples (Part 2).html (0.2 KB)
• 13. Test for the mean. Independent samples (Part 2). Exercise.html (0.1 KB)
• 13.1 4.9.Test-for-the-mean.Independent-samples-Part-2-exercise-2.xlsx (10.5 KB)
• 13.2 4.9.Test-for-the-mean.Independent-samples-Part-2-exercise-2-solution.xlsx (11.4 KB)
• 2. Test for the mean. Population variance known. Exercise.html (0.1 KB)
• 2.1 4.4. Test for the mean. Population variance known_exercise_solution.xlsx (11.2 KB)
• 2.2 4.4. Test for the mean. Population variance known_exercise.xlsx (11.0 KB)
• 3. What is the p-value and why is it one of the most useful tools for statisticians.mp4 (55.9 MB)
• 3. What is the p-value and why is it one of the most useful tools for statisticians.srt (5.0 KB)
• 3.1 Online p-value calculator.pdf (1.2 MB)
• 4. p-value.html (0.2 KB)
• 5. Test for the mean. Population variance unknown.mp4 (40.3 MB)
• 5. Test for the mean. Population variance unknown.srt (5.6 KB)
• 5.1 4.6.Test-for-the-mean.Population-variance-unknown-lesson.xlsx (14.5 KB)
• 6. Test for the mean. Population variance unknown. Exercise.html (0.1 KB)
• 6.1 4.6.Test-for-the-mean.Population-variance-unknown-exercise-solution.xlsx (12.6 KB)
• 6.2 4.6.Test-for-the-mean.Population-variance-unknown-exercise.xlsx (11.3 KB)
• 7. Test for the mean. Dependent samples.mp4 (50.4 MB)
• 7. Test for the mean. Dependent samples.srt (6.3 KB)
• 7.1 4.7. Test for the mean. Dependent samples_lesson.xlsx (9.8 KB)
• 8. Test for the mean. Dependent samples. Exercise.html (0.1 KB)
• 8.1 4.7. Test for the mean. Dependent samples_exercise_solution.xlsx (14.4 KB)
• 8.2 4.7. Test for the mean. Dependent samples_exercise.xlsx (12.8 KB)
• 9. Test for the mean. Independent samples (Part 1).mp4 (30.0 MB)
• 9. Test for the mean. Independent samples (Part 1).srt (5.3 KB)
• 9.1 4.8. Test for the mean. Independent samples (Part 1)_lesson.xlsx (9.6 KB)

• 1. Practical example hypothesis testing.mp4 (69.4 MB)
• 1. Practical example hypothesis testing.srt (8.1 KB)
• 1.1 4.10.Hypothesis-testing-section-practical-example.xlsx (51.7 KB)
• 2. Practical example hypothesis testing.html (0.1 KB)
• 2.1 4.10.Hypothesis-testing-section-practical-example-exercise-solution.xlsx (44.0 KB)
• 2.2 4.10. Hypothesis testing section_practical example_exercise.xlsx (43.4 KB)

• 1. Introduction to regression analysis.mp4 (19.4 MB)
• 1. Introduction to regression analysis.srt (1.5 KB)
• 1.1 Course notes_regression_analysis.pdf (270.1 KB)
• 10. A geometrical representation of the linear regression model.html (0.2 KB)
• 11. A practical example - Reinforced learning.mp4 (45.9 MB)
• 11. A practical example - Reinforced learning.srt (7.4 KB)
• 11.1 5.6. Example_lesson.xlsx (23.5 KB)
• 2. Introduction.html (0.2 KB)
• 3. Correlation and causation.mp4 (25.6 MB)
• 3. Correlation and causation.srt (5.6 KB)
• 3.1 Course notes_regression_analysis.pdf (270.1 KB)
• 3.2 5.2. Correlation and causation_lesson.xlsx (10.6 KB)
• 4. Correlation and causation.html (0.2 KB)
• 5. The linear regression model made easy.mp4 (51.0 MB)
• 5. The linear regression model made easy.srt (7.1 KB)
• 6. The linear regression model.html (0.2 KB)
• 7. What is the difference between correlation and regression.mp4 (12.7 MB)
• 7. What is the difference between correlation and regression.srt (2.1 KB)
• 8. Correlation vs regression.html (0.2 KB)
• 9. A geometrical representation of the linear regression model.mp4 (4.9 MB)
• 9. A geometrical representation of the linear regression model.srt (1.6 KB)

• 1. Decomposing the linear regression model - understanding its nuts and bolts.mp4 (42.2 MB)
• 1. Decomposing the linear regression model - understanding its nuts and bolts.srt (4.2 KB)
• 10. The multiple linear regression model.mp4 (19.1 MB)
• 10. The multiple linear regression model.srt (3.3 KB)
• 11. The multiple linear regression model.html (0.2 KB)
• 12. The adjusted R-squared.mp4 (43.7 MB)
• 12. The adjusted R-squared.srt (6.5 KB)
• 12.1 5.12. Adjusted R-squared_lesson.xlsx (18.2 KB)
• 13. The adjusted R-squared.html (0.2 KB)
• 14. What does the F-statistic show us and why do we need to understand it.mp4 (13.9 MB)
• 14. What does the F-statistic show us and why do we need to understand it.srt (2.6 KB)
• 2. Decomposition.html (0.2 KB)
• 3. What is R-squared and how does it help us.mp4 (36.5 MB)
• 3. What is R-squared and how does it help us.srt (6.4 KB)
• 4. R-squared.html (0.2 KB)
• 5. The ordinary least squares setting and its practical applications.mp4 (20.0 MB)
• 5. The ordinary least squares setting and its practical applications.srt (2.8 KB)
• 6. The ordinary least squares setting and its practical applications.html (0.2 KB)
• 7. Studying regression tables.mp4 (36.8 MB)
• 7. Studying regression tables.srt (6.0 KB)
• 7.1 5.10.Regression-tables-lesson.xlsx (12.5 KB)
• 8. Studying regression tables.html (0.2 KB)
• 9. Regression tables. Exercise.html (0.1 KB)
• 9.1 5.10. Regression tables_exercise.xlsx (12.0 KB)
• 9.2 5.10. Regression tables_exercise_solution.xlsx (12.5 KB)

• 1. OLS assumptions.mp4 (19.4 MB)
• 1. OLS assumptions.srt (3.0 KB)
• 10. A4. No autocorrelation.html (0.2 KB)
• 11. A5. No multicollinearity.mp4 (26.6 MB)
• 11. A5. No multicollinearity.srt (4.6 KB)
• 12. A5. No multicollinearity.html (0.2 KB)
• 2. OLS assumptions.html (0.2 KB)
• 3. A1. Linearity.mp4 (12.1 MB)
• 3. A1. Linearity.srt (2.4 KB)
• 4. A1. Linearity.html (0.2 KB)
• 5. A2. No endogeneity.mp4 (32.5 MB)
• 5. A2. No endogeneity.srt (5.2 KB)
• 6. A2. No endogeneity.html (0.2 KB)
• 7. A3. Normality and homoscedasticity.mp4 (40.0 MB)
• 7. A3. Normality and homoscedasticity.srt (6.7 KB)
• 8. A3. Normality and homoscedasticity.html (0.2 KB)
• 9. A4. No autocorrelation.mp4 (25.9 MB)
• 9. A4. No autocorrelation.srt (4.5 KB)

• 1. Dummy variables.mp4 (38.2 MB)
• 1. Dummy variables.srt (6.1 KB)
• 1.1 5.20. Dummy variables_lesson.xlsx (25.2 KB)

• 1. Practical example regression analysis.mp4 (129.3 MB)
• 1. Practical example regression analysis.srt (17.5 KB)
• 1.1 5.21. Regression_Analysis_practical_example.xlsx (1.4 MB)

• 1. Bonus lecture Next steps.html (3.5 KB)

• 1. Understanding the difference between a population and a sample.mp4 (58.0 MB)
• 1. Understanding the difference between a population and a sample.srt (5.5 KB)
• 1.1 Glossary.xlsx (20.0 KB)
• 1.2 Course notes_descriptive_statistics.pdf (482.2 KB)
• 2. Population vs sample.html (0.2 KB)

• 1. The various types of data we can work with.mp4 (72.6 MB)
• 1. The various types of data we can work with.srt (5.9 KB)
• 1.1 Course notes_descriptive_statistics.pdf (482.2 KB)
• 10. Numerical variables. Using a frequency distribution table. Exercise.html (0.1 KB)
• 10.1 2.4.Numerical-variables.Frequency-distribution-table-exercise.xlsx (12.0 KB)
• 10.2 2.4.Numerical-variables.Frequency-distribution-table-exercise-solution.xlsx (13.3 KB)
• 11. Histogram charts.mp4 (13.8 MB)
• 11. Histogram charts.srt (3.1 KB)
• 11.1 2.5. The Histogram_lesson.xlsx (18.6 KB)
• 12. Histogram charts.html (0.2 KB)
• 13. Histogram charts. Exercise.html (0.1 KB)
• 13.1 Statistics - PDF with Excel Solutions that don't visualize properly.pdf (289.1 KB)
• 13.2 2.5.The-Histogram-exercise-solution.xlsx (17.1 KB)
• 13.3 2.5. The Histogram_exercise.xlsx (15.5 KB)
• 14. Cross tables and scatter plots.mp4 (39.8 MB)
• 14. Cross tables and scatter plots.srt (6.6 KB)
• 14.1 2.6. Cross table and scatter plot.xlsx (26.1 KB)
• 15. Cross Tables and Scatter Plots.html (0.2 KB)
• 16. Cross tables and scatter plots. Exercise.html (0.1 KB)
• 16.1 2.6. Cross table and scatter plot_exercise_solution.xlsx (40.4 KB)
• 16.2 2.6. Cross table and scatter plot_exercise.xlsx (16.3 KB)
• 2. Types of data.html (0.2 KB)
• 3. Levels of measurement.mp4 (54.4 MB)
• 3. Levels of measurement.srt (4.6 KB)
• 4. Levels of measurement.html (0.2 KB)
• 5. Categorical variables. Visualization techniques for categorical variables.mp4 (36.7 MB)
• 5. Categorical variables. Visualization techniques for categorical variables.srt (6.3 KB)
• 5.1 2.3.Categorical-variables.Visualization-techniques-lesson.xlsx (30.8 KB)
• 6. Categorical variables. Visualization Techniques.html (0.2 KB)
• 7. Categorical variables. Visualization techniques. Exercise.html (0.1 KB)
• 7.1 2.3. Categorical variables. Visualization techniques_exercise.xlsx (15.2 KB)
• 7.2 Statistics - PDF with Excel Solutions that don't visualize properly.pdf (289.1 KB)
• 7.3 2.3. Categorical variables. Visualization techniques_exercise_solution.xlsx (41.1 KB)
• 8. Numerical variables. Using a frequency distribution table.mp4 (25.8 MB)
• 8. Numerical variables. Using a frequency distribution table.srt (4.3 KB)
• 8.1 2.4. Numerical variables. Frequency distribution table_lesson.xlsx (11.4 KB)
• 9. Numerical variables. Using a frequency distribution table.html (0.2 KB)

• 1. The main measures of central tendency mean, median and mode.mp4 (37.1 MB)
• 1. The main measures of central tendency mean, median and mode.srt (5.6 KB)
• 1.1 2.7. Mean, median and mode_lesson.xlsx (10.5 KB)
• 10. Standard deviation and coefficient of variation. Exercise.html (0.1 KB)
• 10.1 2.10.Standard-deviation-and-coefficient-of-variation-exercise-solution.xlsx (12.6 KB)
• 10.2 2.10.Standard-deviation-and-coefficient-of-variation-exercise.xlsx (11.6 KB)
• 11. Calculating and understanding covariance.mp4 (27.5 MB)
• 11. Calculating and understanding covariance.srt (4.8 KB)
• 11.1 2.11. Covariance_lesson.xlsx (24.9 KB)
• 12. Covariance. Exercise.html (0.1 KB)
• 12.1 2.11. Covariance_exercise.xlsx (20.2 KB)
• 12.2 2.11. Covariance_exercise_solution.xlsx (29.5 KB)
• 13. The correlation coefficient.mp4 (29.4 MB)
• 13. The correlation coefficient.srt (4.6 KB)
• 13.1 2.12. Correlation_lesson.xlsx (25.0 KB)
• 14. Correlation.html (0.2 KB)
• 15. Correlation coefficient.html (0.1 KB)
• 15.1 2.12. Correlation_exercise_solution.xlsx (29.5 KB)
• 15.2 2.12. Correlation_exercise.xlsx (29.3 KB)
• 2. Mean, median and mode. Exercise.html (0.1 KB)
• 2.1 2.7. Mean, median and mode_exercise_solution.xlsx (11.4 KB)
• 2.2 2.7. Mean, median and mode_exercise.xlsx (10.9 KB)
• 3. Measuring skewness.mp4 (19.4 MB)
• 3. Measuring skewness.srt (3.6 KB)
• 3.1 2.8. Skewness_lesson.xlsx (34.6 KB)
• 4. Skewness.html (0.2 KB)
• 5. Skewness. Exercise.html (0.1 KB)
• 5.1 2.8. Skewness_exercise.xlsx (9.5 KB)
• 5.2 2.8. Skewness_exercise_solution.xlsx (19.8 KB)
• 6. Measuring how data is spread out calculating variance.mp4 (50.9 MB)
• 6. Measuring how data is spread out calculating variance.srt (7.4 KB)
• 6.1 2.9. Variance_lesson.xlsx (10.1 KB)
• 7. Variance. Exercise.html (0.1 KB)
• 7.1 2.9. Variance_exercise.xlsx (10.8 KB)
• 7.2 2.9. Variance_exercise_solution.xlsx (11.1 KB)
• 8. Standard deviation and coefficient of variation.mp4 (45.2 MB)
• 8. Standard deviation and coefficient of variation.srt (6.0 KB)
• 8.1 2.10. Standard deviation and coefficient of variation_lesson.xlsx (11.0 KB)
• 9. Standard deviation.html (0.2 KB)

• 1. Practical example.mp4 (160.5 MB)
• 1. Practical example.srt (19.7 KB)
• 1.1 2.13. Practical example. Descriptive statistics_lesson.xlsx (146.5 KB)
• 2. Practical example descriptive statistics.html (0.1 KB)
• 2.1 2.13.Practical-example.Descriptive-statistics-exercise.xlsx (120.3 KB)
• 2.2 2.13.Practical-example.Descriptive-statistics-exercise-solution.xlsx (146.4 KB)

• 1. Introduction to inferential statistics.mp4 (15.5 MB)
• 1. Introduction to inferential statistics.srt (1.6 KB)
• 1.1 Course notes_inferential statistics.pdf (382.3 KB)
• 10. The central limit theorem.html (0.2 KB)
• 11. Standard error.mp4 (22.8 MB)
• 11. Standard error.srt (1.9 KB)
• 12. Standard error.html (0.2 KB)
• 2. What is a distribution.mp4 (61.6 MB)
• 2. What is a distribution.srt (5.8 KB)
• 2.1 3.2. What is a distribution_lesson.xlsx (19.5 KB)
• 2.2 Course notes_inferential statistics.pdf (382.3 KB)
• 3. What is a distribution.html (0.2 KB)
• 4. The Normal distribution.mp4 (49.9 MB)
• 4. The Normal distribution.srt (5.0 KB)
• 5. The Normal distribution.html (0.2 KB)
• 6. The standard normal distribution.mp4 (22.5 MB)
• 6. The standard normal distribution.srt (3.9 KB)
• 6.1 3.4. Standard normal distribution_lesson.xlsx (10.4 KB)
• 7. The standard normal distribution.html (0.2 KB)
• 8. Standard Normal Distribution. Exercise.html (0.1 KB)
• 8.1 3.4.Standard-normal-distribution-exercise-solution.xlsx (24.0 KB)
• 8.2 3.4.Standard-normal-distribution-exercise.xlsx (12.0 KB)
• 9. Understanding the central limit theorem.mp4 (62.9 MB)
• 9. Understanding the central limit theorem.srt (5.5 KB)

• 1. Working with estimators and estimates.mp4 (47.8 MB)
• 1. Working with estimators and estimates.srt (3.8 KB)
• 10. Calculating confidence intervals within a population with an unknown variance.mp4 (32.2 MB)
• 10. Calculating confidence intervals within a population with an unknown variance.srt (5.1 KB)
• 10.1 3.11. Population variance unknown, t-score_lesson.xlsx (10.8 KB)
• 10.2 3.11. The t-table.xlsx (15.8 KB)
• 11. Population variance unknown. T-score. Exercise.html (0.1 KB)
• 11.1 3.11. Population variance unknown, t-score_exercise_solution.xlsx (11.1 KB)
• 11.2 3.11. The t-table.xlsx (15.8 KB)
• 11.3 3.11. Population variance unknown, t-score_exercise.xlsx (10.6 KB)
• 12. What is a margin of error and why is it important in Statistics.mp4 (47.2 MB)
• 12. What is a margin of error and why is it important in Statistics.srt (6.1 KB)
• 13. Margin of error.html (0.2 KB)
• 2. Estimators and estimates.html (0.2 KB)
• 3. Confidence intervals - an invaluable tool for decision making.mp4 (49.9 MB)
• 3. Confidence intervals - an invaluable tool for decision making.srt (3.0 KB)
• 4. Confidence intervals.html (0.2 KB)
• 5. Calculating confidence intervals within a population with a known variance.mp4 (78.2 MB)
• 5. Calculating confidence intervals within a population with a known variance.srt (9.1 KB)
• 5.1 3.9. Population variance known, z-score_lesson.xlsx (11.2 KB)
• 5.2 3.9.The-z-table.xlsx (25.6 KB)
• 6. Confidence intervals. Population variance known. Exercise.html (0.1 KB)
• 6.1 3.9.The-z-table.xlsx (25.6 KB)
• 6.2 3.9. Population variance known, z-score_exercise.xlsx (10.8 KB)
• 6.3 3.9. Population variance known, z-score_exercise_solution.xlsx (11.2 KB)
• 7. Confidence interval clarifications.mp4 (57.1 MB)
• 7. Confidence interval clarifications.srt (5.5 KB)
• 8. Student's T distribution.mp4 (35.4 MB)
• 8. Student's T distribution.srt (4.2 KB)
• 9. Student's T distribution.html (0.2 KB)

• 1. Calculating confidence intervals for two means with dependent samples.mp4 (70.5 MB)
• 1. Calculating confidence intervals for two means with dependent samples.srt (7.9 KB)
• 1.1 3.13. Confidence intervals. Two means. Dependent samples_lesson.xlsx (10.5 KB)
• 2. Confidence intervals. Two means. Dependent samples. Exercise.html (0.1 KB)
• 2.1 3.13. Confidence intervals. Two means. Dependent samples_exercise.xlsx (13.7 KB)
• 2.2 3.13. Confidence intervals. Two means. Dependent samples_exercise_solution.xlsx (14.2 KB)
• 3. Calculating confidence intervals for two means with independent samples (part 1).mp4 (28.8 MB)
• 3. Calculating confidence intervals for two means with independent samples (part 1).srt (5.9 KB)
• 3.1 3.14. Confidence intervals. Two means. Independent samples (Part 1)_lesson.xlsx (9.8 KB)
• 4. Confidence intervals. Two means. Independent samples (Part 1). Exercise.html (0.1 KB)
• 4.1 3.14. Confidence intervals. Two means. Independent samples (Part 1)_exercise_solution.xlsx (10.1 KB)
• 4.2 3.14. Confidence intervals. Two means. Independent samples (Part 1)_exercise.xlsx (9.8 KB)
• 5. Calculating confidence intervals for two means with independent samples (part 2).mp4 (26.8 MB)
• 5. Calculating confidence intervals for two means with independent samples (part 2).srt (4.4 KB)
• 5.1 3.15. Confidence intervals. Two means. Independent samples (Part 2)_lesson.xlsx (9.5 KB)
• 6. Confidence intervals. Two means. Independent samples (Part 2). Exercise.html (0.1 KB)
• 6.1 3.15. Confidence intervals. Two means. Independent samples (Part 2)_exercise.xlsx (9.2 KB)
• 6.2 3.15. Confidence intervals. Two means. Independent samples (Part 2)_exercise_solution.xlsx (9.8 KB)
• 7. Calculating confidence intervals for two means with independent samples (part 3).mp4 (19.9 MB)
• 7. Calculating confidence intervals for two means with independent samples (part 3).srt (1.9 KB)

• 1. Practical example inferential statistics.mp4 (102.6 MB)
• 1. Practical example inferential statistics.srt (13.3 KB)
• 1.1 3.17. Practical example. Confidence intervals_lesson.xlsx (1.7 MB)
• 2. Practical example inferential statistics.html (0.1 KB)
• 2.1 3.17.Practical-example.Confidence-intervals-exercise-solution.xlsx (1.8 MB)
• 2.2 3.17.Practical-example.Confidence-intervals-exercise.xlsx (1.7 MB)

• Readme.txt (0.9 KB)
• [GigaCourse.com].url (0.0 KB)