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5. Practical example descriptive statistics/1. Practical example.mp4 228.4 MB
17. Practical example regression analysis/1. Practical example regression analysis.mp4 191.9 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 86.5 MB
7. Estimators and estimates/5. Calculating confidence intervals within a population with a known variance.mp4 82.0 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 72.7 MB
6. Distributions/9. Understanding the central limit theorem.mp4 65.9 MB
6. Distributions/2. What is a distribution.mp4 64.6 MB
7. Estimators and estimates/12. What is a margin of error and why is it important in Statistics.mp4 62.1 MB
16. Dealing with categorical data/1. Dummy variables.mp4 60.0 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
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13. The fundamentals of regression analysis/5. The linear regression model made easy.mp4 53.5 MB
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11. Hypothesis testing Let's start testing!/7. Test for the mean. Dependent samples.mp4 52.9 MB
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- 【影视】 Окончательный анализ - Final Analysis (by alenavova).avi
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4. DataFrame Construction/1. Check DataFrame Constructor Input Types.mp4 397.7 MB
1. Project Genesis/2. Pandas Cub Examples.mp4 266.1 MB
2. Environment Setup/4. Installing an IPython Kernel for Jupyter.mp4 255.5 MB
9. Other Methods and Operators/6. Arithmetic and Comparison Operators.mp4 216.2 MB
6. Subset Selection/10. Create a New Column.mp4 195.7 MB
11. Documentation, Strings, and Reading CSVs/2. String-only Methods.mp4 172.9 MB
2. Environment Setup/2. Setting up the Development Environment.mp4 165.2 MB
3. Getting Ready to Code/3. Manually Test in a Jupyter Notebook.mp4 156.9 MB
10. Pivot Tables/1. Pivot Tables Part 1.mp4 154.2 MB
1. Project Genesis/1. Project Overview.mp4 152.9 MB
4. DataFrame Construction/3. Convert Unicode Arrays to Object.mp4 149.3 MB
9. Other Methods and Operators/3. Non-Aggregation Methods.mp4 147.7 MB
2. Environment Setup/3. Test-Driven Development.mp4 146.7 MB
9. Other Methods and Operators/8. The sample Method.mp4 137.9 MB
5. Basic Properties and Visual Representation/5. Visual Notebook Representation.mp4 137.3 MB
6. Subset Selection/6. Select Rows as Booleans, Lists, or Slices.mp4 134.0 MB
5. Basic Properties and Visual Representation/3. Set New Column Names.mp4 133.5 MB
9. Other Methods and Operators/7. The sort_values Method.mp4 129.0 MB
5. Basic Properties and Visual Representation/7. The dtypes Property.mp4 120.3 MB
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15 Business Case/095 Business Case - A Look Into the Automobile Industry.mp4 195.3 MB
13 Auto ARIMA/084 Basic Auto ARIMA Arguments.mp4 91.7 MB
07 Modeling Autoregression The AR Model/036 Fitting Higher-Lag AR Models for Prices.mp4 66.2 MB
14 Forecasting/094 Forecasting Appendix Multivariate Forecasting.mp4 60.5 MB
09 Past Values and Past Errors The ARMA Model/058 ARMA for Prices.mp4 58.7 MB
11 Measuring Volatility The ARCH Model/072 The arch_model Method.mp4 58.6 MB
08 Adjusting to Shocks The MA Model/047 Fitting Higher-Lag MA Models for Returns.mp4 58.6 MB
11 Measuring Volatility The ARCH Model/073 The Simple ARCH Model.mp4 55.5 MB
09 Past Values and Past Errors The ARMA Model/057 Examining the ARMA Model Residuals of Returns.mp4 53.8 MB
14 Forecasting/087 Introduction to Forecasting.mp4 53.7 MB
14 Forecasting/092 Pitfalls of Forecasting.mp4 50.2 MB
01 Introduction/001 What does the course cover.mp4 49.6 MB
03 Introduction to Time Series in Python/010 Introduction to Time-Series Data.mp4 49.5 MB
10 Modeling Non-Stationary Data The ARIMA Model/067 Seasonal Models - SARIMAX.mp4 49.2 MB
10 Modeling Non-Stationary Data The ARIMA Model/060 The Autoregressive Integrated Moving Average (ARIMA) Model.mp4 49.2 MB
05 Working with Time Series in Python/024 White Noise.mp4 48.6 MB
07 Modeling Autoregression The AR Model/033 The Autoregressive (AR) Model.mp4 47.5 MB
09 Past Values and Past Errors The ARMA Model/056 Fitting a Higher-Lag ARMA Model for Returns - Part 3.mp4 45.9 MB
10 Modeling Non-Stationary Data The ARIMA Model/063 Fitting a Higher-Lag ARIMA Model for Prices - Part 2.mp4 45.8 MB
11 Measuring Volatility The ARCH Model/071 A More Detailed Look of the ARCH Model.mp4 45.5 MB
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1. Installation and Setup/6. Mac OS - Update Anaconda Libraries.mp4 37.0 MB
1. Installation and Setup/1. Introduction to the Course.mp4 35.7 MB
10. Working with Dates and Times/16. More Fun with pd.DateOffset Objects.mp4 33.5 MB
4. DataFrames II/2. Filter a DataFrame Based on A Condition.mp4 28.7 MB
9. Merging, Joining, and Concatenating/7. Outer Joins.mp4 27.2 MB
5. DataFrames III/3. Retrieve Rows by Index Label with .loc[].mp4 27.1 MB
10. Working with Dates and Times/15. pd.DateOffset Objects.mp4 26.8 MB
10. Working with Dates and Times/11. Import Financial Data Set with pandas_datareader Library.mp4 26.7 MB
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3. DataFrames I/11. The .astype() Method.mp4 25.0 MB
8. GroupBy/2. First Operations with groupby Object.mp4 24.2 MB
10. Working with Dates and Times/5. The pd.to_datetime() Method.mp4 24.0 MB
9. Merging, Joining, and Concatenating/10. Merging by Indexes with the left_index and right_index Parameters.mp4 23.8 MB
7. MultiIndex/14. The .pivot_table() Method.mp4 23.2 MB
1. Installation and Setup/7. Mac OS - Unpack Course Materials + The Startdown and Shutdown Process.mp4 23.2 MB
8. GroupBy/7. Iterating through Groups.mp4 22.4 MB
2. Series/7. Import Series with the .read_csv() Method.mp4 22.2 MB
7. MultiIndex/2. Create a MultiIndex with the set_index() Method.mp4 22.1 MB
9. Merging, Joining, and Concatenating/8. Left Joins.mp4 22.0 MB
5. DataFrames III/8. Set Multiple Values in DataFrame.mp4 21.6 MB
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015 Joins - Outer, inner, and left vs. right.mp4 17.6 MB
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016 UDFs.mp4 8.5 MB
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011 Joins.mp4 8.2 MB
013 Sort and limit.mp4 7.6 MB
014 Filters.mp4 6.4 MB
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017 Streaming UDF.mp4 4.3 MB
008 Select and aggregate.mp4 4.2 MB
005 MapReduce processing.mp4 3.6 MB
001 Welcome.mp4 3.4 MB
010 Filters.mp4 3.3 MB
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04_04-activity.mp4 47.0 MB
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01_04-BA.mp4 40.3 MB
03_09-enough.mp4 40.2 MB
03_04-brainstorm.mp4 39.1 MB
03_02-gather.mp4 39.0 MB
04_05-accepting.mp4 38.2 MB
01_03-skills.mp4 38.0 MB
05_04-building.mp4 37.8 MB
04_02-exploring.mp4 37.7 MB
03_01-plan.mp4 35.3 MB
01_02-understanding.mp4 34.8 MB
04_01-verifying.mp4 34.6 MB
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006 Analyzing data using variance and standard deviation.mp4 14.7 MB
033 Calculating Bayesian probabilities in Excel.mp4 13.7 MB
019 Using the normal distribution.mp4 13.5 MB
020 Using the exponential distribution.mp4 12.8 MB
021 Using a uniform distribution.mp4 12.4 MB
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014 Forecasting future results.mp4 11.3 MB
027 Visualizing what correlation means.mp4 10.7 MB
022 Using the binomial distribution.mp4 10.5 MB
015 Calculating running averages.mp4 10.5 MB
005 Measuring maximums, minimums, and other data characteristics.mp4 9.8 MB
023 Using the Poisson distribution.mp4 9.7 MB
010 Grouping data using histograms.mp4 9.7 MB
025 Calculating covariance between two columns of data.mp4 9.7 MB
029 Calculating correlation among multiple pairs of columns.mp4 9.6 MB
008 Analyzing a population using data samples.mp4 9.4 MB
012 Visualizing data using logarithmic scales.mp4 8.5 MB
026 Calculating covariance among multiple pairs of columns.mp4 8.4 MB
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13 - 3 - Binary Search Tree Basics, Part II (30 min).mp4 31.4 MB
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