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种子名称： [FreeTutorials.Us] Udemy - statistics-for-data-science-and-business-analysis
文件类型： 视频
文件数目： 63个文件
文件大小： 544.72 MB
收录时间： 2018-7-19 22:02
已经下载： 3次
资源热度： 161
最近下载： 2024-12-13 04:27

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[FreeTutorials.Us] Udemy - statistics-for-data-science-and-business-analysis.torrent

01 Introduction/001 What does the course cover_.mp412.68MB

02 Sample or population data_/002 Understanding the difference between a population and a sample.mp411.36MB

03 The fundamentals of descriptive statistics/003 The various types of data we can work with.mp411.01MB

03 The fundamentals of descriptive statistics/004 Levels of measurement.mp48.8MB

03 The fundamentals of descriptive statistics/005 Categorical variables_ Visualization techniques for categorical variables.mp46.87MB

03 The fundamentals of descriptive statistics/007 Numerical variables_ Using a frequency distribution table.mp45.77MB

03 The fundamentals of descriptive statistics/009 Histogram charts.mp44.27MB

03 The fundamentals of descriptive statistics/011 Cross tables and scatter plots.mp48.65MB

04 Measures of central tendency_ asymmetry_ and variability/013 The main measures of central tendency_ mean_ median_ mode.mp49.98MB

04 Measures of central tendency_ asymmetry_ and variability/015 Measuring skewness.mp44.78MB

04 Measures of central tendency_ asymmetry_ and variability/017 Measuring how data is spread out_ calculating variance.mp48.96MB

04 Measures of central tendency_ asymmetry_ and variability/019 Standard deviation and coefficient of variation.mp410.78MB

04 Measures of central tendency_ asymmetry_ and variability/021 Calculating and understanding covariance.mp45.73MB

04 Measures of central tendency_ asymmetry_ and variability/023 The correlation coefficient.mp48.06MB

05 Practical example_ descriptive statistics/025 Practical example.mp441.29MB

06 Distributions/027 Introduction to inferential statistics.mp42.46MB

06 Distributions/028 What is a distribution_.mp45.64MB

06 Distributions/029 The Normal distribution.mp45.6MB

06 Distributions/030 The standard normal distribution.mp44.58MB

06 Distributions/032 Understanding the central limit theorem.mp49.18MB

06 Distributions/033 Standard error.mp43.01MB

07 Estimators and estimates/034 Working with estimators and estimates.mp44.64MB

07 Estimators and estimates/035 Confidence intervals - an invaluable tool for decision making.mp46.05MB

07 Estimators and estimates/036 Calculating confidence intervals within a population with a known variance.mp412.48MB

07 Estimators and estimates/038 Student's T distribution.mp410.25MB

07 Estimators and estimates/039 Calculating confidence intervals within a population with an unknown variance.mp46.43MB

07 Estimators and estimates/041 What is a margin of error and why is it important in Statistics_.mp410.2MB

08 Confidence intervals_ advanced topics/042 Calculating confidence intervals for two means with dependent samples.mp411.46MB

08 Confidence intervals_ advanced topics/044 Calculating confidence intervals for two means with independent samples (part 1).mp47.03MB

08 Confidence intervals_ advanced topics/046 Calculating confidence intervals for two means with independent samples (part 2).mp46MB

08 Confidence intervals_ advanced topics/048 Calculating confidence intervals for two means with independent samples (part 3).mp42.25MB

09 Practical example_ inferential statistics/049 Practical example_ inferential statistics.mp425.25MB

10 Hypothesis testing_ Introduction/051 The null and the alternative hypothesis.mp49.35MB

10 Hypothesis testing_ Introduction/052 Establishing a rejection region and a significance level.mp47.2MB

10 Hypothesis testing_ Introduction/053 Type I error vs Type II error.mp47.66MB

11 Hypothesis testing_ Let's start testing!/054 Test for the mean_ Population variance known.mp410.73MB

11 Hypothesis testing_ Let's start testing!/056 What is the p-value and why is it one of the most useful tool for statisticians_.mp46.59MB

11 Hypothesis testing_ Let's start testing!/057 Test for the mean_ Population variance unknown.mp47.38MB

11 Hypothesis testing_ Let's start testing!/059 Test for the mean_ Dependent samples.mp47.37MB

11 Hypothesis testing_ Let's start testing!/061 Test for the mean_ Independent samples (Part 1).mp47.88MB

11 Hypothesis testing_ Let's start testing!/062 Test for the mean_ Independent samples (Part 2).mp46.74MB

12 Practical example_ hypothesis testing/064 Practical example_ hypothesis testing.mp419.95MB

13 The fundamentals of regression analysis/066 Introduction to regression analysis.mp41.86MB

13 The fundamentals of regression analysis/067 Correlation and causation.mp47.02MB

13 The fundamentals of regression analysis/068 The linear regression model made easy.mp49.49MB

13 The fundamentals of regression analysis/069 What is the difference between correlation and regression_.mp42.12MB

13 The fundamentals of regression analysis/070 A geometrical representation of the linear regression model.mp41.7MB

13 The fundamentals of regression analysis/071 A practical example - Reinforced learning.mp48.86MB

14 Subtleties of regression analysis/072 Decomposing the linear regression model - understanding its nuts and bolts.mp43.76MB

14 Subtleties of regression analysis/073 What is R-squared and how does it help us_.mp48.31MB

14 Subtleties of regression analysis/074 The ordinary least squares setting and its practical applications.mp44.64MB

14 Subtleties of regression analysis/075 Studying regression tables.mp47.04MB

14 Subtleties of regression analysis/077 The multivariate linear regression model.mp44.44MB

14 Subtleties of regression analysis/078 Adjusted R-squared.mp411.9MB

14 Subtleties of regression analysis/079 What does the F-statistic show us and why we need to understand it_.mp43.08MB

15 Assumptions for linear regression analysis/080 OLS assumptions.mp43.56MB

15 Assumptions for linear regression analysis/081 A1_ Linearity.mp42.55MB

15 Assumptions for linear regression analysis/082 A2_ No endogeneity.mp49.42MB

15 Assumptions for linear regression analysis/083 A3_ Normality and homoscedasticity.mp411.38MB

15 Assumptions for linear regression analysis/084 A4_ No autocorrelation.mp45.44MB

15 Assumptions for linear regression analysis/085 A5_ No multicollinearity.mp45.39MB

16 Dealing with categorical data/086 Dummy variables.mp48MB

17 Practical example_ regression analysis/087 Practical example_ regression analysis.mp442.44MB