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文档列表

06 - Descriptive statistics/004 Code_ data from different distributions.mp4 317.8 MB
16 - Clustering and dimension-reduction/006 Code_ dbscan.mp4 302.1 MB
12 - Correlation/006 Code_ correlation matrix.mp4 296.2 MB
06 - Descriptive statistics/012 Code_ Computing dispersion.mp4 279.0 MB
18 - A real-world data journey/007 Python_ Import and clean the marriage data.mp4 262.0 MB
10 - The t-test family/013 Code_ permutation testing.mp4 252.6 MB
16 - Clustering and dimension-reduction/002 Code_ k-means clustering.mp4 241.5 MB
12 - Correlation/003 Code_ correlation coefficient.mp4 224.5 MB
10 - The t-test family/006 Code_ Two-samples t-test.mp4 221.6 MB
18 - A real-world data journey/003 MATLAB_ Import and clean the marriage data.mp4 211.1 MB
12 - Correlation/018 Code_ Kendall correlation.mp4 193.2 MB
16 - Clustering and dimension-reduction/011 Code_ PCA.mp4 183.6 MB
13 - Analysis of Variance (ANOVA)/008 Code_ One-way ANOVA (independent samples).mp4 181.1 MB
14 - Regression/009 Code_ Multiple regression.mp4 179.3 MB
08 - Probability theory/021 Code_ Law of Large Numbers in action.mp4 173.6 MB
10 - The t-test family/009 Code_ Signed-rank test.mp4 169.7 MB
10 - The t-test family/003 Code_ One-sample t-test.mp4 165.6 MB
08 - Probability theory/015 Code_ sampling variability.mp4 162.3 MB
08 - Probability theory/004 Code_ compute probabilities.mp4 155.6 MB
13 - Analysis of Variance (ANOVA)/001 ANOVA intro, part1.mp4 144.4 MB
18 - A real-world data journey/008 Python_ Import the divorce data.mp4 143.8 MB
07 - Data normalizations and outliers/010 Code_ z-score for outlier removal.mp4 143.5 MB
11 - Confidence intervals on parameters/005 Code_ bootstrapping confidence intervals.mp4 143.4 MB
08 - Probability theory/007 Probability mass vs. density.mp4 140.7 MB
05 - Visualizing data/007 Code_ histograms.mp4 140.0 MB
14 - Regression/011 Code_ polynomial modeling.mp4 135.4 MB
08 - Probability theory/012 Creating sample estimate distributions.mp4 130.9 MB
14 - Regression/015 Under- and over-fitting.mp4 126.7 MB
12 - Correlation/001 Motivation and description of correlation.mp4 124.2 MB
06 - Descriptive statistics/019 Code_ Histogram bins.mp4 123.9 MB
18 - A real-world data journey/009 Python_ Inferential statistics.mp4 121.2 MB
08 - Probability theory/018 Code_ conditional probabilities.mp4 120.7 MB
13 - Analysis of Variance (ANOVA)/011 Code_ Two-way mixed ANOVA.mp4 119.7 MB
18 - A real-world data journey/006 MATLAB_ Inferential statistics.mp4 119.0 MB
16 - Clustering and dimension-reduction/009 Code_ KNN.mp4 113.6 MB
12 - Correlation/010 Code_ partial correlation.mp4 113.5 MB
17 - Signal detection theory/006 F-score.mp4 112.5 MB
09 - Hypothesis testing/004 P-values_ definition, tails, and misinterpretations.mp4 111.6 MB
08 - Probability theory/014 Sampling variability, noise, and other annoyances.mp4 111.2 MB
06 - Descriptive statistics/021 Code_ violin plots.mp4 110.1 MB
13 - Analysis of Variance (ANOVA)/006 The two-way ANOVA.mp4 109.5 MB
12 - Correlation/022 Code_ Cosine similarity vs. Pearson correlation.mp4 107.1 MB
16 - Clustering and dimension-reduction/005 Clustering via dbscan.mp4 105.2 MB
05 - Visualizing data/002 Code_ bar plots.mp4 104.9 MB
06 - Descriptive statistics/024 Code_ entropy.mp4 101.5 MB
18 - A real-world data journey/004 MATLAB_ Import the divorce data.mp4 101.0 MB
08 - Probability theory/010 Code_ cdfs and pdfs.mp4 100.6 MB
11 - Confidence intervals on parameters/003 Code_ compute confidence intervals by formula.mp4 98.9 MB
10 - The t-test family/005 Two-samples t-test.mp4 98.4 MB
08 - Probability theory/023 Code_ the CLT in action.mp4 97.9 MB
09 - Hypothesis testing/001 IVs, DVs, models, and other stats lingo.mp4 95.6 MB
06 - Descriptive statistics/016 Code_ QQ plots.mp4 94.7 MB
09 - Hypothesis testing/008 Parametric vs. non-parametric tests.mp4 91.7 MB
08 - Probability theory/017 Conditional probability.mp4 89.8 MB
13 - Analysis of Variance (ANOVA)/002 ANOVA intro, part 2.mp4 88.3 MB
05 - Visualizing data/004 Code_ box plots.mp4 87.7 MB
06 - Descriptive statistics/014 Code_ IQR.mp4 87.4 MB
14 - Regression/014 Code_ Logistic regression.mp4 85.2 MB
05 - Visualizing data/010 Code_ pie charts.mp4 82.8 MB
14 - Regression/008 Standardizing regression coefficients.mp4 78.8 MB
16 - Clustering and dimension-reduction/014 Code_ ICA.mp4 76.9 MB
13 - Analysis of Variance (ANOVA)/009 Code_ One-way repeated-measures ANOVA.mp4 76.7 MB
12 - Correlation/004 Code_ Simulate data with specified correlation.mp4 73.5 MB
17 - Signal detection theory/003 Code_ d-prime.mp4 72.9 MB
07 - Data normalizations and outliers/003 Code_ z-score.mp4 70.0 MB
06 - Descriptive statistics/009 Code_ computing central tendency.mp4 69.8 MB
08 - Probability theory/008 Code_ compute probability mass functions.mp4 69.4 MB
07 - Data normalizations and outliers/015 Code_ Data trimming to remove outliers.mp4 68.5 MB
17 - Signal detection theory/007 Receiver operating characteristics (ROC).mp4 67.5 MB
10 - The t-test family/012 Permutation testing for t-test significance.mp4 66.6 MB
13 - Analysis of Variance (ANOVA)/005 The omnibus F-test and post-hoc comparisons.mp4 66.4 MB
14 - Regression/001 Introduction to GLM _ regression.mp4 65.0 MB
08 - Probability theory/016 Expected value.mp4 62.5 MB
04 - What are (is_) data_/003 Types of data_ categorical, numerical, etc.mp4 62.2 MB
12 - Correlation/009 Partial correlation.mp4 62.2 MB
17 - Signal detection theory/008 Code_ ROC curves.mp4 57.3 MB
16 - Clustering and dimension-reduction/001 K-means clustering.mp4 56.9 MB
11 - Confidence intervals on parameters/004 Confidence intervals via bootstrapping (resampling).mp4 56.9 MB
06 - Descriptive statistics/011 Measures of dispersion (variance, standard deviation).mp4 56.7 MB
10 - The t-test family/002 One-sample t-test.mp4 56.6 MB
18 - A real-world data journey/002 Introduction.mp4 55.6 MB
14 - Regression/013 Logistic regression.mp4 55.3 MB
14 - Regression/005 Code_ simple regression.mp4 54.8 MB
10 - The t-test family/011 Code_ Mann-Whitney U test.mp4 54.6 MB
09 - Hypothesis testing/002 What is an hypothesis and how do you specify one_.mp4 51.5 MB
01 - Introductions/003 Statistics guessing game_.mp4 50.7 MB
14 - Regression/010 Polynomial regression models.mp4 50.5 MB
04 - What are (is_) data_/004 Code_ representing types of data on computers.mp4 50.2 MB
09 - Hypothesis testing/007 Type 1 and Type 2 errors.mp4 48.1 MB
13 - Analysis of Variance (ANOVA)/003 Sum of squares.mp4 48.1 MB
16 - Clustering and dimension-reduction/013 Independent components analysis (ICA).mp4 47.7 MB
08 - Probability theory/009 Cumulative distribution functions.mp4 47.6 MB
14 - Regression/007 Multiple regression.mp4 47.3 MB
13 - Analysis of Variance (ANOVA)/007 One-way ANOVA example.mp4 46.5 MB
18 - A real-world data journey/010 Take-home messages.mp4 45.9 MB
09 - Hypothesis testing/003 Sample distributions under null and alternative hypotheses.mp4 45.9 MB
05 - Visualizing data/006 Histograms.mp4 45.9 MB
07 - Data normalizations and outliers/013 Code_ Euclidean distance for outlier removal.mp4 45.8 MB
07 - Data normalizations and outliers/007 What are outliers and why are they dangerous_.mp4 45.1 MB
12 - Correlation/014 Code_ Spearman correlation and Fisher-Z.mp4 44.8 MB
16 - Clustering and dimension-reduction/010 Principal components analysis (PCA).mp4 44.6 MB
09 - Hypothesis testing/012 Statistical significance vs. classification accuracy.mp4 44.6 MB
12 - Correlation/002 Covariance and correlation_ formulas.mp4 43.9 MB
14 - Regression/002 Least-squares solution to the GLM.mp4 43.4 MB
08 - Probability theory/001 What is probability_.mp4 43.1 MB
08 - Probability theory/020 The Law of Large Numbers.mp4 42.5 MB
07 - Data normalizations and outliers/005 Code_ min-max scaling.mp4 42.4 MB
15 - Statistical power and sample sizes/001 What is statistical power and why is it important_.mp4 41.4 MB
14 - Regression/017 Comparing _nested_ models.mp4 41.0 MB
06 - Descriptive statistics/007 Measures of central tendency (mean).mp4 40.6 MB
01 - Introductions/001 [Important] Getting the most out of this course.mp4 40.1 MB
14 - Regression/003 Evaluating regression models_ R2 and F.mp4 39.9 MB
08 - Probability theory/003 Computing probabilities.mp4 39.3 MB
08 - Probability theory/002 Probability vs. proportion.mp4 39.3 MB
05 - Visualizing data/013 Code_ line plots.mp4 39.1 MB
04 - What are (is_) data_/005 Sample vs. population data.mp4 38.9 MB
05 - Visualizing data/001 Bar plots.mp4 38.6 MB
14 - Regression/004 Simple regression.mp4 38.6 MB
07 - Data normalizations and outliers/002 Z-score standardization.mp4 38.0 MB
15 - Statistical power and sample sizes/002 Estimating statistical power and sample size.mp4 37.9 MB
13 - Analysis of Variance (ANOVA)/010 Two-way ANOVA example.mp4 37.7 MB
04 - What are (is_) data_/002 Where do data come from and what do they mean_.mp4 37.3 MB
18 - A real-world data journey/005 MATLAB_ More data visualizations.mp4 36.0 MB
06 - Descriptive statistics/008 Measures of central tendency (median, mode).mp4 35.9 MB
17 - Signal detection theory/002 d-prime.mp4 35.8 MB
07 - Data normalizations and outliers/017 Nonlinear data transformations.mp4 35.3 MB
07 - Data normalizations and outliers/008 Removing outliers_ z-score method.mp4 35.1 MB
06 - Descriptive statistics/023 Shannon entropy.mp4 34.7 MB
09 - Hypothesis testing/006 Degrees of freedom.mp4 34.5 MB
10 - The t-test family/014 _Unsupervised learning__ How many permutations_.mp4 34.1 MB
10 - The t-test family/001 Purpose and interpretation of the t-test.mp4 33.7 MB
06 - Descriptive statistics/003 Data distributions.mp4 33.5 MB
15 - Statistical power and sample sizes/003 Compute power and sample size using G_Power.mp4 32.7 MB
12 - Correlation/005 Correlation matrix.mp4 32.5 MB
12 - Correlation/017 Kendall's correlation for ordinal data.mp4 31.6 MB
11 - Confidence intervals on parameters/001 What are confidence intervals and why do we need them_.mp4 31.3 MB
09 - Hypothesis testing/009 Multiple comparisons and Bonferroni correction.mp4 31.0 MB
10 - The t-test family/004 _Unsupervised learning__ The role of variance.mp4 30.0 MB
12 - Correlation/013 Fisher-Z transformation for correlations.mp4 29.9 MB
09 - Hypothesis testing/011 Cross-validation.mp4 29.6 MB
02 - Math prerequisites/001 Should you memorize statistical formulas_.mp4 29.4 MB
01 - Introductions/002 About using MATLAB or Python.mp4 28.4 MB
08 - Probability theory/022 The Central Limit Theorem.mp4 28.0 MB
10 - The t-test family/008 Wilcoxon signed-rank (nonparametric t-test).mp4 27.2 MB
05 - Visualizing data/012 Linear vs. logarithmic axis scaling.mp4 26.9 MB
06 - Descriptive statistics/002 Accuracy, precision, resolution.mp4 26.7 MB
07 - Data normalizations and outliers/012 Multivariate outlier detection.mp4 26.3 MB
01 - Introductions/004 Using the Q&A forum.mp4 25.5 MB
12 - Correlation/012 Nonparametric correlation_ Spearman rank.mp4 24.9 MB
06 - Descriptive statistics/018 Histograms part 2_ Number of bins.mp4 24.6 MB
07 - Data normalizations and outliers/016 Non-parametric solutions to outliers.mp4 24.1 MB
17 - Signal detection theory/005 Code_ Response bias.mp4 23.9 MB
17 - Signal detection theory/004 Response bias.mp4 22.9 MB
06 - Descriptive statistics/017 Statistical _moments_.mp4 22.7 MB
12 - Correlation/020 The subgroups correlation paradox.mp4 22.6 MB
06 - Descriptive statistics/001 Descriptive vs. inferential statistics.mp4 22.5 MB
10 - The t-test family/010 Mann-Whitney U test (nonparametric t-test).mp4 21.3 MB
16 - Clustering and dimension-reduction/007 _Unsupervised learning__ dbscan vs. k-means.mp4 20.9 MB
13 - Analysis of Variance (ANOVA)/004 The F-test and the ANOVA table.mp4 20.9 MB
04 - What are (is_) data_/007 The ethics of making up data.mp4 20.6 MB
09 - Hypothesis testing/010 Statistical vs. theoretical vs. clinical significance.mp4 20.0 MB
11 - Confidence intervals on parameters/007 Misconceptions about confidence intervals.mp4 19.5 MB
12 - Correlation/007 _Unsupervised learning__ average correlation matrices.mp4 19.4 MB
05 - Visualizing data/011 When to use lines instead of bars.mp4 18.9 MB
02 - Math prerequisites/007 The logistic function.mp4 18.8 MB
04 - What are (is_) data_/006 Samples, case reports, and anecdotes.mp4 18.7 MB
07 - Data normalizations and outliers/018 An outlier lecture on personal accountability.mp4 18.6 MB
11 - Confidence intervals on parameters/002 Computing confidence intervals via formula.mp4 18.2 MB
06 - Descriptive statistics/022 _Unsupervised learning__ asymmetric violin plots.mp4 18.2 MB
09 - Hypothesis testing/005 P-z combinations that you should memorize.mp4 18.2 MB
07 - Data normalizations and outliers/014 Removing outliers by data trimming.mp4 17.7 MB
10 - The t-test family/007 _Unsupervised learning__ Importance of N for t-test.mp4 17.6 MB
06 - Descriptive statistics/010 _Unsupervised learning__ central tendencies with outliers.mp4 17.6 MB
12 - Correlation/011 The problem with Pearson.mp4 17.4 MB
05 - Visualizing data/009 Pie charts.mp4 17.3 MB
06 - Descriptive statistics/015 QQ plots.mp4 17.0 MB
14 - Regression/018 What to do about missing data.mp4 16.8 MB
12 - Correlation/015 _Unsupervised learning__ Spearman correlation.mp4 16.7 MB
12 - Correlation/019 _Unsupervised learning__ Does Kendall vs. Pearson matter_.mp4 15.7 MB
03 - IMPORTANT_ Download course materials/001 Download materials for the entire course_.mp4 15.2 MB
12 - Correlation/021 Cosine similarity.mp4 14.9 MB
17 - Signal detection theory/001 The two perspectives of the world.mp4 14.6 MB
08 - Probability theory/019 Tree diagrams for conditional probabilities.mp4 14.2 MB
02 - Math prerequisites/008 Rank and tied-rank.mp4 13.6 MB
16 - Clustering and dimension-reduction/003 _Unsupervised learning__ K-means and normalization.mp4 13.5 MB
02 - Math prerequisites/003 Scientific notation.mp4 13.5 MB
16 - Clustering and dimension-reduction/008 K-nearest neighbor classification.mp4 13.1 MB
02 - Math prerequisites/006 Natural exponent and logarithm.mp4 12.8 MB
08 - Probability theory/005 Probability and odds.mp4 12.6 MB
05 - Visualizing data/008 _Unsupervised learning__ Histogram proportion.mp4 12.4 MB
07 - Data normalizations and outliers/004 Min-max scaling.mp4 12.3 MB
07 - Data normalizations and outliers/001 Garbage in, garbage out (GIGO).mp4 12.1 MB
16 - Clustering and dimension-reduction/012 _Unsupervised learning__ K-means on PC data.mp4 12.1 MB
17 - Signal detection theory/009 _Unsupervised learning__ Make this plot look nicer_.mp4 12.1 MB
05 - Visualizing data/003 Box-and-whisker plots.mp4 11.7 MB
04 - What are (is_) data_/001 Is _data_ singular or plural_______.mp4 11.5 MB
12 - Correlation/016 _Unsupervised learning__ confidence interval on correlation.mp4 10.8 MB
06 - Descriptive statistics/006 The beauty and simplicity of Normal.mp4 10.7 MB
06 - Descriptive statistics/005 _Unsupervised learning__ histograms of distributions.mp4 10.7 MB
12 - Correlation/008 _Unsupervised learning__ correlation to covariance matrix.mp4 10.6 MB
06 - Descriptive statistics/013 Interquartile range (IQR).mp4 10.3 MB
07 - Data normalizations and outliers/009 The modified z-score method.mp4 10.1 MB
08 - Probability theory/024 _Unsupervised learning__ Averaging pairs of numbers.mp4 9.9 MB
08 - Probability theory/011 _Unsupervised learning__ cdf's for various distributions.mp4 9.8 MB
07 - Data normalizations and outliers/011 _Unsupervised learning__ z vs. modified-z.mp4 9.5 MB
08 - Probability theory/013 Monte Carlo sampling.mp4 9.3 MB
11 - Confidence intervals on parameters/006 _Unsupervised learning__ Confidence intervals for variance.mp4 9.0 MB
06 - Descriptive statistics/025 _Unsupervised learning__ entropy and number of bins.mp4 8.7 MB
05 - Visualizing data/005 _Unsupervised learning__ Boxplots of normal and uniform noise.mp4 8.6 MB
16 - Clustering and dimension-reduction/004 _Unsupervised learning__ K-means on a Gauss blur.mp4 8.3 MB
02 - Math prerequisites/004 Summation notation.mp4 8.1 MB
02 - Math prerequisites/002 Arithmetic and exponents.mp4 7.9 MB
01 - Introductions/005 (optional) Entering time-stamped notes in the Udemy video player.mp4 7.4 MB
02 - Math prerequisites/005 Absolute value.mp4 7.3 MB
07 - Data normalizations and outliers/006 _Unsupervised learning__ Invert the min-max scaling.mp4 7.1 MB
06 - Descriptive statistics/020 Violin plots.mp4 6.8 MB
08 - Probability theory/006 _Unsupervised learning__ probabilities of odds-space.mp4 6.2 MB
14 - Regression/006 _Unsupervised learning__ Compute R2 and F.mp4 5.6 MB
14 - Regression/016 _Unsupervised learning__ Overfit data.mp4 5.1 MB
14 - Regression/012 _Unsupervised learning__ Polynomial design matrix.mp4 5.0 MB
05 - Visualizing data/014 _Unsupervised learning__ log-scaled plots.mp4 3.9 MB
03 - IMPORTANT_ Download course materials/32684220-statsML.zip 1.4 MB
16 - Clustering and dimension-reduction/006 Code_ dbscan_en.srt 50.6 kB
06 - Descriptive statistics/004 Code_ data from different distributions_en.srt 47.0 kB
16 - Clustering and dimension-reduction/006 Code_ dbscan_en.vtt 43.2 kB
12 - Correlation/003 Code_ correlation coefficient_en.srt 41.4 kB
06 - Descriptive statistics/004 Code_ data from different distributions_en.vtt 40.4 kB
08 - Probability theory/015 Code_ sampling variability_en.srt 39.2 kB
06 - Descriptive statistics/012 Code_ Computing dispersion_en.srt 38.1 kB
10 - The t-test family/013 Code_ permutation testing_en.srt 38.0 kB
12 - Correlation/003 Code_ correlation coefficient_en.vtt 35.5 kB
16 - Clustering and dimension-reduction/002 Code_ k-means clustering_en.srt 35.2 kB
07 - Data normalizations and outliers/010 Code_ z-score for outlier removal_en.srt 34.5 kB
17 - Signal detection theory/006 F-score_en.srt 33.9 kB
08 - Probability theory/015 Code_ sampling variability_en.vtt 33.7 kB
06 - Descriptive statistics/012 Code_ Computing dispersion_en.vtt 33.1 kB
10 - The t-test family/006 Code_ Two-samples t-test_en.srt 32.9 kB
12 - Correlation/006 Code_ correlation matrix_en.srt 32.6 kB
10 - The t-test family/013 Code_ permutation testing_en.vtt 32.5 kB
12 - Correlation/022 Code_ Cosine similarity vs. Pearson correlation_en.srt 32.0 kB
10 - The t-test family/003 Code_ One-sample t-test_en.srt 32.0 kB
06 - Descriptive statistics/024 Code_ entropy_en.srt 31.0 kB
14 - Regression/001 Introduction to GLM _ regression_en.srt 30.4 kB
08 - Probability theory/018 Code_ conditional probabilities_en.srt 30.3 kB
12 - Correlation/010 Code_ partial correlation_en.srt 30.1 kB
16 - Clustering and dimension-reduction/002 Code_ k-means clustering_en.vtt 30.1 kB
13 - Analysis of Variance (ANOVA)/006 The two-way ANOVA_en.srt 30.1 kB
18 - A real-world data journey/007 Python_ Import and clean the marriage data_en.srt 30.0 kB
07 - Data normalizations and outliers/010 Code_ z-score for outlier removal_en.vtt 29.5 kB
17 - Signal detection theory/006 F-score_en.vtt 29.4 kB
13 - Analysis of Variance (ANOVA)/002 ANOVA intro, part 2_en.srt 29.1 kB
14 - Regression/009 Code_ Multiple regression_en.srt 28.6 kB
08 - Probability theory/021 Code_ Law of Large Numbers in action_en.srt 28.5 kB
08 - Probability theory/012 Creating sample estimate distributions_en.srt 28.4 kB
10 - The t-test family/006 Code_ Two-samples t-test_en.vtt 28.2 kB
12 - Correlation/001 Motivation and description of correlation_en.srt 28.0 kB
12 - Correlation/006 Code_ correlation matrix_en.vtt 27.8 kB
12 - Correlation/022 Code_ Cosine similarity vs. Pearson correlation_en.vtt 27.6 kB
10 - The t-test family/009 Code_ Signed-rank test_en.srt 27.5 kB
10 - The t-test family/003 Code_ One-sample t-test_en.vtt 27.3 kB
16 - Clustering and dimension-reduction/011 Code_ PCA_en.srt 27.2 kB
06 - Descriptive statistics/011 Measures of dispersion (variance, standard deviation)_en.srt 26.9 kB
13 - Analysis of Variance (ANOVA)/001 ANOVA intro, part1_en.srt 26.8 kB
06 - Descriptive statistics/024 Code_ entropy_en.vtt 26.5 kB
13 - Analysis of Variance (ANOVA)/008 Code_ One-way ANOVA (independent samples)_en.srt 26.3 kB
11 - Confidence intervals on parameters/003 Code_ compute confidence intervals by formula_en.srt 26.3 kB
13 - Analysis of Variance (ANOVA)/003 Sum of squares_en.srt 26.2 kB
14 - Regression/001 Introduction to GLM _ regression_en.vtt 26.1 kB
18 - A real-world data journey/007 Python_ Import and clean the marriage data_en.vtt 26.1 kB
14 - Regression/013 Logistic regression_en.srt 26.1 kB
09 - Hypothesis testing/004 P-values_ definition, tails, and misinterpretations_en.srt 26.0 kB
05 - Visualizing data/002 Code_ bar plots_en.srt 26.0 kB
14 - Regression/015 Under- and over-fitting_en.srt 26.0 kB
08 - Probability theory/018 Code_ conditional probabilities_en.vtt 26.0 kB
12 - Correlation/010 Code_ partial correlation_en.vtt 25.8 kB
13 - Analysis of Variance (ANOVA)/006 The two-way ANOVA_en.vtt 25.8 kB
13 - Analysis of Variance (ANOVA)/002 ANOVA intro, part 2_en.vtt 25.2 kB
09 - Hypothesis testing/001 IVs, DVs, models, and other stats lingo_en.srt 24.9 kB
05 - Visualizing data/007 Code_ histograms_en.srt 24.8 kB
14 - Regression/009 Code_ Multiple regression_en.vtt 24.5 kB
08 - Probability theory/021 Code_ Law of Large Numbers in action_en.vtt 24.4 kB
08 - Probability theory/012 Creating sample estimate distributions_en.vtt 24.4 kB
14 - Regression/003 Evaluating regression models_ R2 and F_en.srt 24.4 kB
18 - A real-world data journey/35855730-state-marriage-rates-90-95-99-19.xlsx 24.2 kB
08 - Probability theory/023 Code_ the CLT in action_en.srt 24.1 kB
12 - Correlation/001 Motivation and description of correlation_en.vtt 24.1 kB
18 - A real-world data journey/003 MATLAB_ Import and clean the marriage data_en.srt 24.1 kB
06 - Descriptive statistics/016 Code_ QQ plots_en.srt 24.0 kB
06 - Descriptive statistics/014 Code_ IQR_en.srt 24.0 kB
09 - Hypothesis testing/002 What is an hypothesis and how do you specify one__en.srt 23.8 kB
16 - Clustering and dimension-reduction/010 Principal components analysis (PCA)_en.srt 23.8 kB
10 - The t-test family/009 Code_ Signed-rank test_en.vtt 23.6 kB
12 - Correlation/018 Code_ Kendall correlation_en.vtt 23.5 kB
05 - Visualizing data/002 Code_ bar plots_en.vtt 23.2 kB
13 - Analysis of Variance (ANOVA)/001 ANOVA intro, part1_en.vtt 23.2 kB
16 - Clustering and dimension-reduction/011 Code_ PCA_en.vtt 23.1 kB
06 - Descriptive statistics/011 Measures of dispersion (variance, standard deviation)_en.vtt 23.1 kB
18 - A real-world data journey/35855734-state-divorce-rates-90-95-99-19.xlsx 23.0 kB
14 - Regression/011 Code_ polynomial modeling_en.srt 23.0 kB
13 - Analysis of Variance (ANOVA)/003 Sum of squares_en.vtt 22.9 kB
09 - Hypothesis testing/004 P-values_ definition, tails, and misinterpretations_en.vtt 22.8 kB
09 - Hypothesis testing/007 Type 1 and Type 2 errors_en.srt 22.7 kB
11 - Confidence intervals on parameters/003 Code_ compute confidence intervals by formula_en.vtt 22.6 kB
08 - Probability theory/004 Code_ compute probabilities_en.srt 22.6 kB
13 - Analysis of Variance (ANOVA)/008 Code_ One-way ANOVA (independent samples)_en.vtt 22.5 kB
17 - Signal detection theory/003 Code_ d-prime_en.srt 22.4 kB
14 - Regression/013 Logistic regression_en.vtt 22.3 kB
14 - Regression/015 Under- and over-fitting_en.vtt 22.2 kB
16 - Clustering and dimension-reduction/005 Clustering via dbscan_en.srt 22.2 kB
11 - Confidence intervals on parameters/005 Code_ bootstrapping confidence intervals_en.srt 22.2 kB
07 - Data normalizations and outliers/007 What are outliers and why are they dangerous__en.srt 22.1 kB
13 - Analysis of Variance (ANOVA)/011 Code_ Two-way mixed ANOVA_en.srt 22.0 kB
16 - Clustering and dimension-reduction/001 K-means clustering_en.srt 21.5 kB
04 - What are (is_) data_/003 Types of data_ categorical, numerical, etc_en.srt 21.4 kB
09 - Hypothesis testing/001 IVs, DVs, models, and other stats lingo_en.vtt 21.4 kB
05 - Visualizing data/007 Code_ histograms_en.vtt 21.3 kB
12 - Correlation/002 Covariance and correlation_ formulas_en.srt 21.3 kB
13 - Analysis of Variance (ANOVA)/007 One-way ANOVA example_en.srt 21.1 kB
18 - A real-world data journey/003 MATLAB_ Import and clean the marriage data_en.vtt 21.0 kB
14 - Regression/003 Evaluating regression models_ R2 and F_en.vtt 21.0 kB
08 - Probability theory/009 Cumulative distribution functions_en.srt 20.9 kB
08 - Probability theory/023 Code_ the CLT in action_en.vtt 20.8 kB
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06 - Descriptive statistics/005 _Unsupervised learning__ histograms of distributions_en.srt 3.1 kB
05 - Visualizing data/008 _Unsupervised learning__ Histogram proportion_en.vtt 3.0 kB
12 - Correlation/019 _Unsupervised learning__ Does Kendall vs. Pearson matter__en.vtt 3.0 kB
08 - Probability theory/011 _Unsupervised learning__ cdf's for various distributions_en.vtt 3.0 kB
12 - Correlation/016 _Unsupervised learning__ confidence interval on correlation_en.vtt 3.0 kB
08 - Probability theory/006 _Unsupervised learning__ probabilities of odds-space_en.vtt 2.8 kB
08 - Probability theory/024 _Unsupervised learning__ Averaging pairs of numbers_en.vtt 2.8 kB
14 - Regression/016 _Unsupervised learning__ Overfit data_en.srt 2.8 kB
01 - Introductions/005 (optional) Entering time-stamped notes in the Udemy video player_en.vtt 2.7 kB
06 - Descriptive statistics/005 _Unsupervised learning__ histograms of distributions_en.vtt 2.7 kB
09 - Hypothesis testing/006 Degrees of freedom_en.srt 2.7 kB
16 - Clustering and dimension-reduction/003 _Unsupervised learning__ K-means and normalization_en.srt 2.5 kB
05 - Visualizing data/014 _Unsupervised learning__ log-scaled plots_en.srt 2.5 kB
14 - Regression/016 _Unsupervised learning__ Overfit data_en.vtt 2.4 kB
17 - Signal detection theory/009 _Unsupervised learning__ Make this plot look nicer__en.srt 2.4 kB
04 - What are (is_) data_/001 Is _data_ singular or plural________en.srt 2.4 kB
16 - Clustering and dimension-reduction/012 _Unsupervised learning__ K-means on PC data_en.srt 2.3 kB
16 - Clustering and dimension-reduction/003 _Unsupervised learning__ K-means and normalization_en.vtt 2.2 kB
05 - Visualizing data/014 _Unsupervised learning__ log-scaled plots_en.vtt 2.2 kB
17 - Signal detection theory/009 _Unsupervised learning__ Make this plot look nicer__en.vtt 2.1 kB
04 - What are (is_) data_/001 Is _data_ singular or plural________en.vtt 2.1 kB
06 - Descriptive statistics/025 _Unsupervised learning__ entropy and number of bins_en.srt 2.1 kB
16 - Clustering and dimension-reduction/004 _Unsupervised learning__ K-means on a Gauss blur_en.srt 2.0 kB
16 - Clustering and dimension-reduction/012 _Unsupervised learning__ K-means on PC data_en.vtt 2.0 kB
11 - Confidence intervals on parameters/006 _Unsupervised learning__ Confidence intervals for variance_en.srt 1.9 kB
12 - Correlation/015 _Unsupervised learning__ Spearman correlation_en.srt 1.9 kB
06 - Descriptive statistics/025 _Unsupervised learning__ entropy and number of bins_en.vtt 1.8 kB
16 - Clustering and dimension-reduction/004 _Unsupervised learning__ K-means on a Gauss blur_en.vtt 1.8 kB
11 - Confidence intervals on parameters/006 _Unsupervised learning__ Confidence intervals for variance_en.vtt 1.7 kB
12 - Correlation/015 _Unsupervised learning__ Spearman correlation_en.vtt 1.7 kB
14 - Regression/006 _Unsupervised learning__ Compute R2 and F_en.srt 1.5 kB
14 - Regression/006 _Unsupervised learning__ Compute R2 and F_en.vtt 1.3 kB
14 - Regression/012 _Unsupervised learning__ Polynomial design matrix_en.srt 1.1 kB
14 - Regression/012 _Unsupervised learning__ Polynomial design matrix_en.vtt 1.0 kB
19 - Bonus section/001 About deep learning.html 619 Bytes
18 - A real-world data journey/001 Note about the code for this section.html 135 Bytes
01 - Introductions/[Tutorialsplanet.NET].url 128 Bytes
12 - Correlation/[Tutorialsplanet.NET].url 128 Bytes
19 - Bonus section/[Tutorialsplanet.NET].url 128 Bytes
[Tutorialsplanet.NET].url 128 Bytes

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