种子简介

种子名称： [UdemyCourseDownloader] Statistics for Data Science and Business Analysis
文件类型： 视频
文件数目： 45个文件
文件大小： 1.88 GB
收录时间： 2020-10-18 10:37
已经下载： 3次
资源热度： 241
最近下载： 2025-1-15 17:43

下载BT种子文件

下载Torrent文件(.torrent) 立即下载

磁力链接下载

magnet:?xt=urn:btih:cd4019836ee4425ea11e7057f70aadd09bfa69c2&dn=[UdemyCourseDownloader] Statistics for Data Science and Business Analysis 复制链接到迅雷、QQ旋风进行下载，或者使用百度云离线下载。

喜欢这个种子的人也喜欢

种子包含的文件

[UdemyCourseDownloader] Statistics for Data Science and Business Analysis.torrent

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

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

02. Sample or population data/1. Understanding the difference between a population and a sample.mp458.05MB

03. The fundamentals of descriptive statistics/1. The various types of data we can work with.mp472.6MB

03. The fundamentals of descriptive statistics/3. Levels of measurement.mp454.38MB

03. The fundamentals of descriptive statistics/5. Categorical variables. Visualization techniques for categorical variables.mp438.48MB

03. The fundamentals of descriptive statistics/8. Numerical variables. Using a frequency distribution table.mp425.84MB

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

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

04. Measures of central tendency, asymmetry, and variability/1. The main measures of central tendency mean, median and mode.mp437.12MB

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

04. Measures of central tendency, asymmetry, and variability/6. Measuring how data is spread out calculating variance.mp450.94MB

04. Measures of central tendency, asymmetry, and variability/8. Standard deviation and coefficient of variation.mp445.21MB

04. Measures of central tendency, asymmetry, and variability/11. Calculating and understanding covariance.mp427.48MB

04. Measures of central tendency, asymmetry, and variability/14. The correlation coefficient.mp429.41MB

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

10. Hypothesis testing Introduction/1. The null and the alternative hypothesis.mp492.16MB

10. Hypothesis testing Introduction/4. Establishing a rejection region and a significance level.mp4112.69MB

10. Hypothesis testing Introduction/6. Type I error vs Type II error.mp443.93MB

11. Hypothesis testing Let's start testing!/1. Test for the mean. Population variance known.mp454.3MB

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.mp455.88MB

11. Hypothesis testing Let's start testing!/5. Test for the mean. Population variance unknown.mp440.26MB

11. Hypothesis testing Let's start testing!/7. Test for the mean. Dependent samples.mp450.45MB

11. Hypothesis testing Let's start testing!/9. Test for the mean. Independent samples (Part 1).mp429.97MB

11. Hypothesis testing Let's start testing!/11. Test for the mean. Independent samples (Part 2).mp436.39MB

12. Practical example hypothesis testing/1. Practical example hypothesis testing.mp469.39MB

13. The fundamentals of regression analysis/1. Introduction to regression analysis.mp419.41MB

13. The fundamentals of regression analysis/3. Correlation and causation.mp425.58MB

13. The fundamentals of regression analysis/5. The linear regression model made easy.mp450.99MB

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

13. The fundamentals of regression analysis/11. A practical example - Reinforced learning.mp445.88MB

14. Subtleties of regression analysis/1. Decomposing the linear regression model - understanding its nuts and bolts.mp442.22MB

14. Subtleties of regression analysis/5. The ordinary least squares setting and its practical applications.mp420.05MB

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

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

14. Subtleties of regression analysis/12. The adjusted R-squared.mp443.71MB

14. Subtleties of regression analysis/14. What does the F-statistic show us and why do we need to understand it.mp413.9MB

15. Assumptions for linear regression analysis/1. OLS assumptions.mp419.39MB

15. Assumptions for linear regression analysis/3. A1. Linearity.mp412.06MB

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

15. Assumptions for linear regression analysis/7. A3. Normality and homoscedasticity.mp439.97MB

15. Assumptions for linear regression analysis/9. A4. No autocorrelation.mp425.89MB

15. Assumptions for linear regression analysis/11. A5. No multicollinearity.mp426.59MB

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