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03. The fundamentals of descriptive statistics/8. Numerical variables. Using a frequency distribution table.mp4
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04. Measures of central tendency, asymmetry, and variability/14. The correlation coefficient.mp4
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09. Practical example inferential statistics/1. Practical example inferential statistics.mp4
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10. Hypothesis testing Introduction/1. The null and the alternative hypothesis.mp4
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15. Assumptions for linear regression analysis/7. A3. Normality and homoscedasticity.vtt
6.11KB
15. Assumptions for linear regression analysis/8. A3. Normality and homoscedasticity.html
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15. Assumptions for linear regression analysis/9. A4. No autocorrelation.mp4
25.89MB
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15. Assumptions for linear regression analysis/9. A4. No autocorrelation.vtt
4.19KB
15. Assumptions for linear regression analysis/10. A4. No autocorrelation.html
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15. Assumptions for linear regression analysis/11. A5. No multicollinearity.mp4
26.59MB
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15. Assumptions for linear regression analysis/11. A5. No multicollinearity.vtt
4.3KB
15. Assumptions for linear regression analysis/12. A5. No multicollinearity.html
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16. Dealing with categorical data/1. Dummy variables.mp4
38.18MB
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16. Dealing with categorical data/1. Dummy variables.vtt
5.76KB
16. Dealing with categorical data/1.1 5.20. Dummy variables_lesson.xlsx.xlsx
25.19KB
Udemy Course downloader.txt
94B
17. Practical example regression analysis/1. Practical example regression analysis.vtt
15.98KB
17. Practical example regression analysis/1.1 5.21. Regression_Analysis_practical_example.xlsx.xlsx
1.44MB
18. Bonus lecture/1. Bonus lecture Next steps.html
3.52KB