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5. Practical example descriptive statistics/1. Practical example.mp4 168.3 MB
17. Practical example regression analysis/1. Practical example regression analysis.mp4 135.6 MB
9. Practical example inferential statistics/1. Practical example inferential statistics.mp4 107.6 MB
10. Hypothesis testing Introduction/1. The null and the alternative hypothesis.mp4 96.6 MB
10. Hypothesis testing Introduction/4. Establishing a rejection region and a significance level.mp4 86.6 MB
7. Estimators and estimates/5. Calculating confidence intervals within a population with a known variance.mp4 82.0 MB
3. The fundamentals of descriptive statistics/1. The various types of data we can work with.mp4 76.1 MB
8. Confidence intervals advanced topics/1. Calculating confidence intervals for two means with dependent samples.mp4 73.9 MB
12. Practical example hypothesis testing/1. Practical example hypothesis testing.mp4 72.8 MB
1. Introduction/1. What does the course cover.mp4 72.0 MB
6. Distributions/9. Understanding the central limit theorem.mp4 66.0 MB
6. Distributions/2. What is a distribution.mp4 64.6 MB
2. Sample or population data/1. Understanding the difference between a population and a sample.mp4 60.9 MB
7. Estimators and estimates/7. Confidence interval clarifications.mp4 59.9 MB
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 58.6 MB
3. The fundamentals of descriptive statistics/3. Levels of measurement.mp4 57.0 MB
11. Hypothesis testing Let's start testing!/1. Test for the mean. Population variance known.mp4 56.9 MB
13. The fundamentals of regression analysis/5. The linear regression model made easy.mp4 53.5 MB
4. Measures of central tendency, asymmetry, and variability/6. Measuring how data is spread out calculating variance.mp4 53.4 MB
11. Hypothesis testing Let's start testing!/7. Test for the mean. Dependent samples.mp4 52.9 MB
7. Estimators and estimates/3. Confidence intervals - an invaluable tool for decision making.mp4 52.4 MB
6. Distributions/4. The Normal distribution.mp4 52.3 MB
7. Estimators and estimates/1. Working with estimators and estimates.mp4 50.2 MB
7. Estimators and estimates/12. What is a margin of error and why is it important in Statistics.mp4 49.5 MB
13. The fundamentals of regression analysis/11. A practical example - Reinforced learning.mp4 48.1 MB
4. Measures of central tendency, asymmetry, and variability/8. Standard deviation and coefficient of variation.mp4 47.4 MB
10. Hypothesis testing Introduction/6. Type I error vs Type II error.mp4 46.1 MB
14. Subtleties of regression analysis/12. The adjusted R-squared.mp4 45.8 MB
14. Subtleties of regression analysis/1. Decomposing the linear regression model - understanding its nuts and bolts.mp4 44.3 MB
11. Hypothesis testing Let's start testing!/5. Test for the mean. Population variance unknown.mp4 42.2 MB
15. Assumptions for linear regression analysis/7. A3. Normality and homoscedasticity.mp4 41.9 MB
3. The fundamentals of descriptive statistics/14. Cross tables and scatter plots.mp4 41.7 MB
16. Dealing with categorical data/1. Dummy variables.mp4 40.0 MB
4. Measures of central tendency, asymmetry, and variability/1. The main measures of central tendency mean, median and mode.mp4 38.9 MB
14. Subtleties of regression analysis/7. Studying regression tables.mp4 38.6 MB
3. The fundamentals of descriptive statistics/5. Categorical variables. Visualization techniques for categorical variables.mp4 38.4 MB
14. Subtleties of regression analysis/3. What is R-squared and how does it help us.mp4 38.2 MB
11. Hypothesis testing Let's start testing!/11. Test for the mean. Independent samples (Part 2).mp4 38.2 MB
7. Estimators and estimates/8. Student's T distribution.mp4 37.1 MB
15. Assumptions for linear regression analysis/5. A2. No endogeneity.mp4 34.0 MB
7. Estimators and estimates/10. Calculating confidence intervals within a population with an unknown variance.mp4 33.8 MB
11. Hypothesis testing Let's start testing!/9. Test for the mean. Independent samples (Part 1).mp4 31.4 MB
4. Measures of central tendency, asymmetry, and variability/13. The correlation coefficient.mp4 30.8 MB
8. Confidence intervals advanced topics/3. Calculating confidence intervals for two means with independent samples (part 1).mp4 30.1 MB
4. Measures of central tendency, asymmetry, and variability/11. Calculating and understanding covariance.mp4 28.8 MB
8. Confidence intervals advanced topics/5. Calculating confidence intervals for two means with independent samples (part 2).mp4 28.1 MB
15. Assumptions for linear regression analysis/11. A5. No multicollinearity.mp4 27.9 MB
15. Assumptions for linear regression analysis/9. A4. No autocorrelation.mp4 27.1 MB
3. The fundamentals of descriptive statistics/8. Numerical variables. Using a frequency distribution table.mp4 27.1 MB
13. The fundamentals of regression analysis/3. Correlation and causation.mp4 26.8 MB
6. Distributions/11. Standard error.mp4 23.9 MB
6. Distributions/6. The standard normal distribution.mp4 23.6 MB
14. Subtleties of regression analysis/5. The ordinary least squares setting and its practical applications.mp4 21.0 MB
8. Confidence intervals advanced topics/7. Calculating confidence intervals for two means with independent samples (part 3).mp4 20.9 MB
4. Measures of central tendency, asymmetry, and variability/3. Measuring skewness.mp4 20.4 MB
13. The fundamentals of regression analysis/1. Introduction to regression analysis.mp4 20.3 MB
15. Assumptions for linear regression analysis/1. OLS assumptions.mp4 20.3 MB
14. Subtleties of regression analysis/10. The multiple linear regression model.mp4 20.0 MB
6. Distributions/1. Introduction to inferential statistics.mp4 16.2 MB
14. Subtleties of regression analysis/14. What does the F-statistic show us and why do we need to understand it.mp4 14.6 MB
3. The fundamentals of descriptive statistics/11. Histogram charts.mp4 14.5 MB
13. The fundamentals of regression analysis/7. What is the difference between correlation and regression.mp4 13.3 MB
15. Assumptions for linear regression analysis/3. A1. Linearity.mp4 12.6 MB
2. Sample or population data/1.2 Course notes_descriptive_statistics_jp2.zip 7.5 MB
3. The fundamentals of descriptive statistics/1.1 Course notes_descriptive_statistics_jp2.zip 7.5 MB
3. The fundamentals of descriptive statistics/13.1 Statistics - PDF with Excel Solutions that don't visualize properly_jp2.zip 5.6 MB
3. The fundamentals of descriptive statistics/7.2 Statistics - PDF with Excel Solutions that don't visualize properly_jp2.zip 5.6 MB
10. Hypothesis testing Introduction/1.1 Course notes_hypothesis_testing_jp2.zip 5.4 MB
10. Hypothesis testing Introduction/4.1 Course notes_hypothesis_testing_jp2.zip 5.4 MB
13. The fundamentals of regression analysis/9. A geometrical representation of the linear regression model.mp4 5.1 MB
11. Hypothesis testing Let's start testing!/3.1 Online p-value calculator_jp2.zip 5.1 MB
13. The fundamentals of regression analysis/1.1 Course notes_regression_analysis_jp2.zip 4.1 MB
13. The fundamentals of regression analysis/3.1 Course notes_regression_analysis_jp2.zip 4.1 MB
6. Distributions/1.1 Course notes_inferential statistics_jp2.zip 2.3 MB
6. Distributions/2.2 Course notes_inferential statistics_jp2.zip 2.3 MB
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