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种子名称： [FreeAllCourse.Com] Udemy - Statistics for Data Science and Business Analysis
文件类型： 视频
文件数目： 64个文件
文件大小： 2.76 GB
收录时间： 2023-10-21 19:19
已经下载： 3次
资源热度： 95
最近下载： 2024-5-10 00:05

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[FreeAllCourse.Com] Udemy - Statistics for Data Science and Business Analysis.torrent

1. Introduction/1. What does the course cover.mp468.63MB

10. Hypothesis testing Introduction/1. The null and the alternative hypothesis.mp492.15MB

10. Hypothesis testing Introduction/4. Establishing a rejection region and a significance level.mp482.53MB

10. Hypothesis testing Introduction/6. Type I error vs Type II error.mp443.94MB

11. Hypothesis testing Let's start testing!/1. Test for the mean. Population variance known.mp454.29MB

11. Hypothesis testing Let's start testing!/11. Test for the mean. Independent samples (Part 2).mp436.38MB

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

11. Hypothesis testing Let's start testing!/5. Test for the mean. Population variance unknown.mp440.25MB

11. Hypothesis testing Let's start testing!/7. Test for the mean. Dependent samples.mp450.44MB

11. Hypothesis testing Let's start testing!/9. Test for the mean. Independent samples (Part 1).mp429.96MB

12. Practical example hypothesis testing/1. Practical example hypothesis testing.mp469.38MB

13. The fundamentals of regression analysis/1. Introduction to regression analysis.mp419.4MB

13. The fundamentals of regression analysis/11. A practical example - Reinforced learning.mp445.87MB

13. The fundamentals of regression analysis/3. Correlation and causation.mp425.57MB

13. The fundamentals of regression analysis/5. The linear regression model made easy.mp450.98MB

13. The fundamentals of regression analysis/7. What is the difference between correlation and regression.mp412.71MB

13. The fundamentals of regression analysis/9. A geometrical representation of the linear regression model.mp44.91MB

14. Subtleties of regression analysis/1. Decomposing the linear regression model - understanding its nuts and bolts.mp442.21MB

14. Subtleties of regression analysis/10. The multiple linear regression model.mp419.1MB

14. Subtleties of regression analysis/12. The adjusted R-squared.mp443.7MB

14. Subtleties of regression analysis/14. What does the F-statistic show us and why do we need to understand it.mp413.91MB

14. Subtleties of regression analysis/3. What is R-squared and how does it help us.mp436.44MB

14. Subtleties of regression analysis/5. The ordinary least squares setting and its practical applications.mp420.04MB

14. Subtleties of regression analysis/7. Studying regression tables.mp436.78MB

15. Assumptions for linear regression analysis/1. OLS assumptions.mp419.38MB

15. Assumptions for linear regression analysis/11. A5. No multicollinearity.mp426.58MB

15. Assumptions for linear regression analysis/3. A1. Linearity.mp412.05MB

15. Assumptions for linear regression analysis/5. A2. No endogeneity.mp432.44MB

15. Assumptions for linear regression analysis/7. A3. Normality and homoscedasticity.mp439.96MB

15. Assumptions for linear regression analysis/9. A4. No autocorrelation.mp425.88MB

16. Dealing with categorical data/1. Dummy variables.mp438.18MB

17. Practical example regression analysis/1. Practical example regression analysis.mp4129.31MB

2. Sample or population data/1. Understanding the difference between a population and a sample.mp458.04MB

3. The fundamentals of descriptive statistics/1. The various types of data we can work with.mp472.58MB

3. The fundamentals of descriptive statistics/11. Histogram charts.mp413.79MB

3. The fundamentals of descriptive statistics/14. Cross tables and scatter plots.mp439.8MB

3. The fundamentals of descriptive statistics/3. Levels of measurement.mp454.37MB

3. The fundamentals of descriptive statistics/5. Categorical variables. Visualization techniques for categorical variables.mp438.47MB

3. The fundamentals of descriptive statistics/8. Numerical variables. Using a frequency distribution table.mp425.85MB

4. Measures of central tendency, asymmetry, and variability/1. The main measures of central tendency mean, median and mode.mp437.11MB

4. Measures of central tendency, asymmetry, and variability/11. Calculating and understanding covariance.mp427.47MB

4. Measures of central tendency, asymmetry, and variability/13. The correlation coefficient.mp429.4MB

4. Measures of central tendency, asymmetry, and variability/3. Measuring skewness.mp419.41MB

4. Measures of central tendency, asymmetry, and variability/6. Measuring how data is spread out calculating variance.mp450.93MB

4. Measures of central tendency, asymmetry, and variability/8. Standard deviation and coefficient of variation.mp445.2MB

5. Practical example descriptive statistics/1. Practical example.mp4160.46MB

6. Distributions/1. Introduction to inferential statistics.mp415.47MB

6. Distributions/11. Standard error.mp422.76MB

6. Distributions/2. What is a distribution.mp461.61MB

6. Distributions/4. The Normal distribution.mp449.86MB

6. Distributions/6. The standard normal distribution.mp422.5MB

6. Distributions/9. Understanding the central limit theorem.mp462.89MB

7. Estimators and estimates/1. Working with estimators and estimates.mp447.83MB

7. Estimators and estimates/10. Calculating confidence intervals within a population with an unknown variance.mp432.18MB

7. Estimators and estimates/12. What is a margin of error and why is it important in Statistics.mp447.21MB

7. Estimators and estimates/3. Confidence intervals - an invaluable tool for decision making.mp449.94MB

7. Estimators and estimates/5. Calculating confidence intervals within a population with a known variance.mp478.21MB

7. Estimators and estimates/7. Confidence interval clarifications.mp457.11MB

7. Estimators and estimates/8. Student's T distribution.mp435.4MB

8. Confidence intervals advanced topics/1. Calculating confidence intervals for two means with dependent samples.mp470.49MB

8. Confidence intervals advanced topics/3. Calculating confidence intervals for two means with independent samples (part 1).mp428.75MB

8. Confidence intervals advanced topics/5. Calculating confidence intervals for two means with independent samples (part 2).mp426.81MB

8. Confidence intervals advanced topics/7. Calculating confidence intervals for two means with independent samples (part 3).mp419.89MB

9. Practical example inferential statistics/1. Practical example inferential statistics.mp4102.59MB