[Tutorialsplanet.NET] Udemy - Master statistics & machine learning - intuition, math, code

Creation Time	Oct. 18, 2024, 2:43 a.m.
Last Access Time	Nov. 23, 2024, 7:39 a.m.
File Size	12.8 GB
Keywords	Tutorialsplanet intuition statistics - Udemy machine code Master learning NET math
Total Requests	10
Total Files	674
Magnet Link	Please wait ...
	Download (Magnet Link) Play (Watch Online)

06 - Descriptive statistics/004 Code_ data from different distributions.mp4 303.1 MB
16 - Clustering and dimension-reduction/006 Code_ dbscan.mp4 288.1 MB
12 - Correlation/006 Code_ correlation matrix.mp4 282.5 MB
06 - Descriptive statistics/012 Code_ Computing dispersion.mp4 266.1 MB
18 - A real-world data journey/007 Python_ Import and clean the marriage data.mp4 249.8 MB
10 - The t-test family/013 Code_ permutation testing.mp4 240.9 MB
16 - Clustering and dimension-reduction/002 Code_ k-means clustering.mp4 230.3 MB
12 - Correlation/003 Code_ correlation coefficient.mp4 214.1 MB
10 - The t-test family/006 Code_ Two-samples t-test.mp4 211.3 MB
18 - A real-world data journey/003 MATLAB_ Import and clean the marriage data.mp4 201.3 MB
12 - Correlation/018 Code_ Kendall correlation.mp4 184.2 MB
16 - Clustering and dimension-reduction/011 Code_ PCA.mp4 175.1 MB
13 - Analysis of Variance (ANOVA)/008 Code_ One-way ANOVA (independent samples).mp4 172.7 MB
14 - Regression/009 Code_ Multiple regression.mp4 171.0 MB
08 - Probability theory/021 Code_ Law of Large Numbers in action.mp4 165.6 MB
10 - The t-test family/009 Code_ Signed-rank test.mp4 161.8 MB
10 - The t-test family/003 Code_ One-sample t-test.mp4 158.0 MB
08 - Probability theory/015 Code_ sampling variability.mp4 154.8 MB
08 - Probability theory/004 Code_ compute probabilities.mp4 148.4 MB
13 - Analysis of Variance (ANOVA)/001 ANOVA intro, part1.mp4 137.7 MB
18 - A real-world data journey/008 Python_ Import the divorce data.mp4 137.1 MB
07 - Data normalizations and outliers/010 Code_ z-score for outlier removal.mp4 136.9 MB
11 - Confidence intervals on parameters/005 Code_ bootstrapping confidence intervals.mp4 136.7 MB
08 - Probability theory/007 Probability mass vs. density.mp4 134.1 MB
05 - Visualizing data/007 Code_ histograms.mp4 133.5 MB
14 - Regression/011 Code_ polynomial modeling.mp4 129.1 MB
08 - Probability theory/012 Creating sample estimate distributions.mp4 124.8 MB
14 - Regression/015 Under- and over-fitting.mp4 120.9 MB
12 - Correlation/001 Motivation and description of correlation.mp4 118.4 MB
06 - Descriptive statistics/019 Code_ Histogram bins.mp4 118.1 MB
18 - A real-world data journey/009 Python_ Inferential statistics.mp4 115.5 MB
08 - Probability theory/018 Code_ conditional probabilities.mp4 115.1 MB
13 - Analysis of Variance (ANOVA)/011 Code_ Two-way mixed ANOVA.mp4 114.2 MB
18 - A real-world data journey/006 MATLAB_ Inferential statistics.mp4 113.5 MB
16 - Clustering and dimension-reduction/009 Code_ KNN.mp4 108.3 MB
12 - Correlation/010 Code_ partial correlation.mp4 108.3 MB
17 - Signal detection theory/006 F-score.mp4 107.3 MB
09 - Hypothesis testing/004 P-values_ definition, tails, and misinterpretations.mp4 106.5 MB
08 - Probability theory/014 Sampling variability, noise, and other annoyances.mp4 106.1 MB
06 - Descriptive statistics/021 Code_ violin plots.mp4 105.0 MB
13 - Analysis of Variance (ANOVA)/006 The two-way ANOVA.mp4 104.4 MB
12 - Correlation/022 Code_ Cosine similarity vs. Pearson correlation.mp4 102.2 MB
16 - Clustering and dimension-reduction/005 Clustering via dbscan.mp4 100.3 MB
05 - Visualizing data/002 Code_ bar plots.mp4 100.0 MB
06 - Descriptive statistics/024 Code_ entropy.mp4 96.8 MB
18 - A real-world data journey/004 MATLAB_ Import the divorce data.mp4 96.3 MB
08 - Probability theory/010 Code_ cdfs and pdfs.mp4 95.9 MB
11 - Confidence intervals on parameters/003 Code_ compute confidence intervals by formula.mp4 94.3 MB
10 - The t-test family/005 Two-samples t-test.mp4 93.8 MB
08 - Probability theory/023 Code_ the CLT in action.mp4 93.3 MB
09 - Hypothesis testing/001 IVs, DVs, models, and other stats lingo.mp4 91.1 MB
06 - Descriptive statistics/016 Code_ QQ plots.mp4 90.3 MB
09 - Hypothesis testing/008 Parametric vs. non-parametric tests.mp4 87.5 MB
08 - Probability theory/017 Conditional probability.mp4 85.7 MB
13 - Analysis of Variance (ANOVA)/002 ANOVA intro, part 2.mp4 84.2 MB
05 - Visualizing data/004 Code_ box plots.mp4 83.7 MB
06 - Descriptive statistics/014 Code_ IQR.mp4 83.4 MB
14 - Regression/014 Code_ Logistic regression.mp4 81.2 MB
05 - Visualizing data/010 Code_ pie charts.mp4 78.9 MB
14 - Regression/008 Standardizing regression coefficients.mp4 75.2 MB
16 - Clustering and dimension-reduction/014 Code_ ICA.mp4 73.4 MB
13 - Analysis of Variance (ANOVA)/009 Code_ One-way repeated-measures ANOVA.mp4 73.1 MB
12 - Correlation/004 Code_ Simulate data with specified correlation.mp4 70.1 MB
17 - Signal detection theory/003 Code_ d-prime.mp4 69.5 MB
07 - Data normalizations and outliers/003 Code_ z-score.mp4 66.8 MB
06 - Descriptive statistics/009 Code_ computing central tendency.mp4 66.6 MB
08 - Probability theory/008 Code_ compute probability mass functions.mp4 66.2 MB
07 - Data normalizations and outliers/015 Code_ Data trimming to remove outliers.mp4 65.3 MB
17 - Signal detection theory/007 Receiver operating characteristics (ROC).mp4 64.4 MB
10 - The t-test family/012 Permutation testing for t-test significance.mp4 63.5 MB
13 - Analysis of Variance (ANOVA)/005 The omnibus F-test and post-hoc comparisons.mp4 63.4 MB
14 - Regression/001 Introduction to GLM _ regression.mp4 62.0 MB
08 - Probability theory/016 Expected value.mp4 59.6 MB
04 - What are (is_) data_/003 Types of data_ categorical, numerical, etc.mp4 59.4 MB
12 - Correlation/009 Partial correlation.mp4 59.3 MB
17 - Signal detection theory/008 Code_ ROC curves.mp4 54.6 MB
16 - Clustering and dimension-reduction/001 K-means clustering.mp4 54.3 MB
11 - Confidence intervals on parameters/004 Confidence intervals via bootstrapping (resampling).mp4 54.3 MB
06 - Descriptive statistics/011 Measures of dispersion (variance, standard deviation).mp4 54.1 MB
10 - The t-test family/002 One-sample t-test.mp4 53.9 MB
18 - A real-world data journey/002 Introduction.mp4 53.0 MB
14 - Regression/013 Logistic regression.mp4 52.7 MB
14 - Regression/005 Code_ simple regression.mp4 52.3 MB
10 - The t-test family/011 Code_ Mann-Whitney U test.mp4 52.0 MB
09 - Hypothesis testing/002 What is an hypothesis and how do you specify one_.mp4 49.1 MB
01 - Introductions/003 Statistics guessing game_.mp4 48.4 MB
14 - Regression/010 Polynomial regression models.mp4 48.2 MB
04 - What are (is_) data_/004 Code_ representing types of data on computers.mp4 47.8 MB
09 - Hypothesis testing/007 Type 1 and Type 2 errors.mp4 45.9 MB
13 - Analysis of Variance (ANOVA)/003 Sum of squares.mp4 45.9 MB
16 - Clustering and dimension-reduction/013 Independent components analysis (ICA).mp4 45.5 MB
08 - Probability theory/009 Cumulative distribution functions.mp4 45.4 MB
14 - Regression/007 Multiple regression.mp4 45.1 MB
13 - Analysis of Variance (ANOVA)/007 One-way ANOVA example.mp4 44.3 MB
18 - A real-world data journey/010 Take-home messages.mp4 43.8 MB
09 - Hypothesis testing/003 Sample distributions under null and alternative hypotheses.mp4 43.8 MB
05 - Visualizing data/006 Histograms.mp4 43.7 MB
07 - Data normalizations and outliers/013 Code_ Euclidean distance for outlier removal.mp4 43.7 MB
07 - Data normalizations and outliers/007 What are outliers and why are they dangerous_.mp4 43.0 MB
12 - Correlation/014 Code_ Spearman correlation and Fisher-Z.mp4 42.7 MB
16 - Clustering and dimension-reduction/010 Principal components analysis (PCA).mp4 42.6 MB
09 - Hypothesis testing/012 Statistical significance vs. classification accuracy.mp4 42.5 MB
12 - Correlation/002 Covariance and correlation_ formulas.mp4 41.9 MB
14 - Regression/002 Least-squares solution to the GLM.mp4 41.4 MB
08 - Probability theory/001 What is probability_.mp4 41.1 MB
08 - Probability theory/020 The Law of Large Numbers.mp4 40.6 MB
07 - Data normalizations and outliers/005 Code_ min-max scaling.mp4 40.4 MB
15 - Statistical power and sample sizes/001 What is statistical power and why is it important_.mp4 39.5 MB
14 - Regression/017 Comparing _nested_ models.mp4 39.1 MB
06 - Descriptive statistics/007 Measures of central tendency (mean).mp4 38.7 MB
01 - Introductions/001 [Important] Getting the most out of this course.mp4 38.3 MB
14 - Regression/003 Evaluating regression models_ R2 and F.mp4 38.1 MB
08 - Probability theory/003 Computing probabilities.mp4 37.5 MB
08 - Probability theory/002 Probability vs. proportion.mp4 37.5 MB
05 - Visualizing data/013 Code_ line plots.mp4 37.3 MB
04 - What are (is_) data_/005 Sample vs. population data.mp4 37.1 MB
05 - Visualizing data/001 Bar plots.mp4 36.8 MB
14 - Regression/004 Simple regression.mp4 36.8 MB
07 - Data normalizations and outliers/002 Z-score standardization.mp4 36.2 MB
15 - Statistical power and sample sizes/002 Estimating statistical power and sample size.mp4 36.2 MB
13 - Analysis of Variance (ANOVA)/010 Two-way ANOVA example.mp4 35.9 MB
04 - What are (is_) data_/002 Where do data come from and what do they mean_.mp4 35.5 MB
18 - A real-world data journey/005 MATLAB_ More data visualizations.mp4 34.3 MB
06 - Descriptive statistics/008 Measures of central tendency (median, mode).mp4 34.3 MB
17 - Signal detection theory/002 d-prime.mp4 34.1 MB
07 - Data normalizations and outliers/017 Nonlinear data transformations.mp4 33.7 MB
07 - Data normalizations and outliers/008 Removing outliers_ z-score method.mp4 33.5 MB
06 - Descriptive statistics/023 Shannon entropy.mp4 33.0 MB
09 - Hypothesis testing/006 Degrees of freedom.mp4 32.9 MB
10 - The t-test family/014 _Unsupervised learning__ How many permutations_.mp4 32.5 MB
10 - The t-test family/001 Purpose and interpretation of the t-test.mp4 32.2 MB
06 - Descriptive statistics/003 Data distributions.mp4 32.0 MB
15 - Statistical power and sample sizes/003 Compute power and sample size using G_Power.mp4 31.2 MB
12 - Correlation/005 Correlation matrix.mp4 31.0 MB
12 - Correlation/017 Kendall's correlation for ordinal data.mp4 30.1 MB
11 - Confidence intervals on parameters/001 What are confidence intervals and why do we need them_.mp4 29.8 MB
09 - Hypothesis testing/009 Multiple comparisons and Bonferroni correction.mp4 29.6 MB
10 - The t-test family/004 _Unsupervised learning__ The role of variance.mp4 28.6 MB
12 - Correlation/013 Fisher-Z transformation for correlations.mp4 28.5 MB
09 - Hypothesis testing/011 Cross-validation.mp4 28.2 MB
02 - Math prerequisites/001 Should you memorize statistical formulas_.mp4 28.0 MB
01 - Introductions/002 About using MATLAB or Python.mp4 27.1 MB
08 - Probability theory/022 The Central Limit Theorem.mp4 26.7 MB
10 - The t-test family/008 Wilcoxon signed-rank (nonparametric t-test).mp4 26.0 MB
05 - Visualizing data/012 Linear vs. logarithmic axis scaling.mp4 25.6 MB
06 - Descriptive statistics/002 Accuracy, precision, resolution.mp4 25.4 MB
07 - Data normalizations and outliers/012 Multivariate outlier detection.mp4 25.0 MB
01 - Introductions/004 Using the Q&A forum.mp4 24.4 MB
12 - Correlation/012 Nonparametric correlation_ Spearman rank.mp4 23.7 MB
06 - Descriptive statistics/018 Histograms part 2_ Number of bins.mp4 23.5 MB
07 - Data normalizations and outliers/016 Non-parametric solutions to outliers.mp4 23.0 MB
17 - Signal detection theory/005 Code_ Response bias.mp4 22.8 MB
17 - Signal detection theory/004 Response bias.mp4 21.8 MB
06 - Descriptive statistics/017 Statistical _moments_.mp4 21.7 MB
12 - Correlation/020 The subgroups correlation paradox.mp4 21.6 MB
06 - Descriptive statistics/001 Descriptive vs. inferential statistics.mp4 21.5 MB
10 - The t-test family/010 Mann-Whitney U test (nonparametric t-test).mp4 20.3 MB
16 - Clustering and dimension-reduction/007 _Unsupervised learning__ dbscan vs. k-means.mp4 19.9 MB
13 - Analysis of Variance (ANOVA)/004 The F-test and the ANOVA table.mp4 19.9 MB
04 - What are (is_) data_/007 The ethics of making up data.mp4 19.7 MB
09 - Hypothesis testing/010 Statistical vs. theoretical vs. clinical significance.mp4 19.1 MB
11 - Confidence intervals on parameters/007 Misconceptions about confidence intervals.mp4 18.6 MB
12 - Correlation/007 _Unsupervised learning__ average correlation matrices.mp4 18.5 MB
05 - Visualizing data/011 When to use lines instead of bars.mp4 18.0 MB
02 - Math prerequisites/007 The logistic function.mp4 17.9 MB
04 - What are (is_) data_/006 Samples, case reports, and anecdotes.mp4 17.8 MB
07 - Data normalizations and outliers/018 An outlier lecture on personal accountability.mp4 17.7 MB
11 - Confidence intervals on parameters/002 Computing confidence intervals via formula.mp4 17.3 MB
06 - Descriptive statistics/022 _Unsupervised learning__ asymmetric violin plots.mp4 17.3 MB
09 - Hypothesis testing/005 P-z combinations that you should memorize.mp4 17.3 MB
07 - Data normalizations and outliers/014 Removing outliers by data trimming.mp4 16.9 MB
10 - The t-test family/007 _Unsupervised learning__ Importance of N for t-test.mp4 16.8 MB
06 - Descriptive statistics/010 _Unsupervised learning__ central tendencies with outliers.mp4 16.7 MB
12 - Correlation/011 The problem with Pearson.mp4 16.6 MB
05 - Visualizing data/009 Pie charts.mp4 16.5 MB
06 - Descriptive statistics/015 QQ plots.mp4 16.2 MB
14 - Regression/018 What to do about missing data.mp4 16.0 MB
12 - Correlation/015 _Unsupervised learning__ Spearman correlation.mp4 16.0 MB
12 - Correlation/019 _Unsupervised learning__ Does Kendall vs. Pearson matter_.mp4 14.9 MB
03 - IMPORTANT_ Download course materials/001 Download materials for the entire course_.mp4 14.5 MB
12 - Correlation/021 Cosine similarity.mp4 14.2 MB
17 - Signal detection theory/001 The two perspectives of the world.mp4 13.9 MB
08 - Probability theory/019 Tree diagrams for conditional probabilities.mp4 13.5 MB
02 - Math prerequisites/008 Rank and tied-rank.mp4 12.9 MB
16 - Clustering and dimension-reduction/003 _Unsupervised learning__ K-means and normalization.mp4 12.9 MB
02 - Math prerequisites/003 Scientific notation.mp4 12.9 MB
16 - Clustering and dimension-reduction/008 K-nearest neighbor classification.mp4 12.5 MB
02 - Math prerequisites/006 Natural exponent and logarithm.mp4 12.2 MB
08 - Probability theory/005 Probability and odds.mp4 12.0 MB
05 - Visualizing data/008 _Unsupervised learning__ Histogram proportion.mp4 11.8 MB
07 - Data normalizations and outliers/004 Min-max scaling.mp4 11.7 MB
07 - Data normalizations and outliers/001 Garbage in, garbage out (GIGO).mp4 11.5 MB
16 - Clustering and dimension-reduction/012 _Unsupervised learning__ K-means on PC data.mp4 11.5 MB
17 - Signal detection theory/009 _Unsupervised learning__ Make this plot look nicer_.mp4 11.5 MB
05 - Visualizing data/003 Box-and-whisker plots.mp4 11.1 MB
04 - What are (is_) data_/001 Is _data_ singular or plural_______.mp4 10.9 MB
12 - Correlation/016 _Unsupervised learning__ confidence interval on correlation.mp4 10.3 MB
06 - Descriptive statistics/006 The beauty and simplicity of Normal.mp4 10.2 MB
06 - Descriptive statistics/005 _Unsupervised learning__ histograms of distributions.mp4 10.2 MB
12 - Correlation/008 _Unsupervised learning__ correlation to covariance matrix.mp4 10.1 MB
06 - Descriptive statistics/013 Interquartile range (IQR).mp4 9.8 MB
07 - Data normalizations and outliers/009 The modified z-score method.mp4 9.6 MB
08 - Probability theory/024 _Unsupervised learning__ Averaging pairs of numbers.mp4 9.5 MB
08 - Probability theory/011 _Unsupervised learning__ cdf's for various distributions.mp4 9.3 MB
07 - Data normalizations and outliers/011 _Unsupervised learning__ z vs. modified-z.mp4 9.0 MB
08 - Probability theory/013 Monte Carlo sampling.mp4 8.8 MB
11 - Confidence intervals on parameters/006 _Unsupervised learning__ Confidence intervals for variance.mp4 8.5 MB
06 - Descriptive statistics/025 _Unsupervised learning__ entropy and number of bins.mp4 8.3 MB
05 - Visualizing data/005 _Unsupervised learning__ Boxplots of normal and uniform noise.mp4 8.2 MB
16 - Clustering and dimension-reduction/004 _Unsupervised learning__ K-means on a Gauss blur.mp4 7.9 MB
02 - Math prerequisites/004 Summation notation.mp4 7.7 MB
02 - Math prerequisites/002 Arithmetic and exponents.mp4 7.6 MB
01 - Introductions/005 (optional) Entering time-stamped notes in the Udemy video player.mp4 7.1 MB
02 - Math prerequisites/005 Absolute value.mp4 6.9 MB
07 - Data normalizations and outliers/006 _Unsupervised learning__ Invert the min-max scaling.mp4 6.8 MB
06 - Descriptive statistics/020 Violin plots.mp4 6.5 MB
08 - Probability theory/006 _Unsupervised learning__ probabilities of odds-space.mp4 5.9 MB
14 - Regression/006 _Unsupervised learning__ Compute R2 and F.mp4 5.4 MB
14 - Regression/016 _Unsupervised learning__ Overfit data.mp4 4.8 MB
14 - Regression/012 _Unsupervised learning__ Polynomial design matrix.mp4 4.7 MB
05 - Visualizing data/014 _Unsupervised learning__ log-scaled plots.mp4 3.7 MB
03 - IMPORTANT_ Download course materials/32684220-statsML.zip 1.4 MB
16 - Clustering and dimension-reduction/006 Code_ dbscan_en.srt 49.4 KB
06 - Descriptive statistics/004 Code_ data from different distributions_en.srt 45.9 KB
16 - Clustering and dimension-reduction/006 Code_ dbscan_en.vtt 42.2 KB
12 - Correlation/003 Code_ correlation coefficient_en.srt 40.4 KB
06 - Descriptive statistics/004 Code_ data from different distributions_en.vtt 39.5 KB
08 - Probability theory/015 Code_ sampling variability_en.srt 38.3 KB
06 - Descriptive statistics/012 Code_ Computing dispersion_en.srt 37.2 KB
10 - The t-test family/013 Code_ permutation testing_en.srt 37.1 KB
12 - Correlation/003 Code_ correlation coefficient_en.vtt 34.6 KB
16 - Clustering and dimension-reduction/002 Code_ k-means clustering_en.srt 34.3 KB
07 - Data normalizations and outliers/010 Code_ z-score for outlier removal_en.srt 33.6 KB
17 - Signal detection theory/006 F-score_en.srt 33.1 KB
08 - Probability theory/015 Code_ sampling variability_en.vtt 32.9 KB
06 - Descriptive statistics/012 Code_ Computing dispersion_en.vtt 32.3 KB
10 - The t-test family/006 Code_ Two-samples t-test_en.srt 32.2 KB
12 - Correlation/006 Code_ correlation matrix_en.srt 31.9 KB
10 - The t-test family/013 Code_ permutation testing_en.vtt 31.8 KB
12 - Correlation/022 Code_ Cosine similarity vs. Pearson correlation_en.srt 31.3 KB
10 - The t-test family/003 Code_ One-sample t-test_en.srt 31.2 KB
06 - Descriptive statistics/024 Code_ entropy_en.srt 30.3 KB
14 - Regression/001 Introduction to GLM _ regression_en.srt 29.7 KB
08 - Probability theory/018 Code_ conditional probabilities_en.srt 29.6 KB
12 - Correlation/010 Code_ partial correlation_en.srt 29.4 KB
16 - Clustering and dimension-reduction/002 Code_ k-means clustering_en.vtt 29.4 KB
13 - Analysis of Variance (ANOVA)/006 The two-way ANOVA_en.srt 29.4 KB
18 - A real-world data journey/007 Python_ Import and clean the marriage data_en.srt 29.3 KB
07 - Data normalizations and outliers/010 Code_ z-score for outlier removal_en.vtt 28.8 KB
17 - Signal detection theory/006 F-score_en.vtt 28.8 KB
13 - Analysis of Variance (ANOVA)/002 ANOVA intro, part 2_en.srt 28.4 KB
14 - Regression/009 Code_ Multiple regression_en.srt 27.9 KB
08 - Probability theory/021 Code_ Law of Large Numbers in action_en.srt 27.8 KB
08 - Probability theory/012 Creating sample estimate distributions_en.srt 27.7 KB
10 - The t-test family/006 Code_ Two-samples t-test_en.vtt 27.6 KB
12 - Correlation/001 Motivation and description of correlation_en.srt 27.4 KB
12 - Correlation/006 Code_ correlation matrix_en.vtt 27.2 KB
12 - Correlation/022 Code_ Cosine similarity vs. Pearson correlation_en.vtt 26.9 KB
10 - The t-test family/009 Code_ Signed-rank test_en.srt 26.9 KB
10 - The t-test family/003 Code_ One-sample t-test_en.vtt 26.6 KB
16 - Clustering and dimension-reduction/011 Code_ PCA_en.srt 26.5 KB
06 - Descriptive statistics/011 Measures of dispersion (variance, standard deviation)_en.srt 26.3 KB
13 - Analysis of Variance (ANOVA)/001 ANOVA intro, part1_en.srt 26.2 KB
06 - Descriptive statistics/024 Code_ entropy_en.vtt 25.8 KB
13 - Analysis of Variance (ANOVA)/008 Code_ One-way ANOVA (independent samples)_en.srt 25.7 KB
11 - Confidence intervals on parameters/003 Code_ compute confidence intervals by formula_en.srt 25.7 KB
13 - Analysis of Variance (ANOVA)/003 Sum of squares_en.srt 25.6 KB
14 - Regression/001 Introduction to GLM _ regression_en.vtt 25.5 KB
18 - A real-world data journey/007 Python_ Import and clean the marriage data_en.vtt 25.5 KB
14 - Regression/013 Logistic regression_en.srt 25.5 KB
09 - Hypothesis testing/004 P-values_ definition, tails, and misinterpretations_en.srt 25.4 KB
05 - Visualizing data/002 Code_ bar plots_en.srt 25.4 KB
14 - Regression/015 Under- and over-fitting_en.srt 25.4 KB
08 - Probability theory/018 Code_ conditional probabilities_en.vtt 25.4 KB
12 - Correlation/010 Code_ partial correlation_en.vtt 25.2 KB
13 - Analysis of Variance (ANOVA)/006 The two-way ANOVA_en.vtt 25.2 KB
13 - Analysis of Variance (ANOVA)/002 ANOVA intro, part 2_en.vtt 24.6 KB
09 - Hypothesis testing/001 IVs, DVs, models, and other stats lingo_en.srt 24.3 KB
05 - Visualizing data/007 Code_ histograms_en.srt 24.2 KB
14 - Regression/009 Code_ Multiple regression_en.vtt 23.9 KB
08 - Probability theory/021 Code_ Law of Large Numbers in action_en.vtt 23.8 KB
08 - Probability theory/012 Creating sample estimate distributions_en.vtt 23.8 KB
14 - Regression/003 Evaluating regression models_ R2 and F_en.srt 23.8 KB
18 - A real-world data journey/35855730-state-marriage-rates-90-95-99-19.xlsx 23.6 KB
08 - Probability theory/023 Code_ the CLT in action_en.srt 23.6 KB
12 - Correlation/001 Motivation and description of correlation_en.vtt 23.6 KB
18 - A real-world data journey/003 MATLAB_ Import and clean the marriage data_en.srt 23.6 KB
06 - Descriptive statistics/016 Code_ QQ plots_en.srt 23.5 KB
06 - Descriptive statistics/014 Code_ IQR_en.srt 23.4 KB
09 - Hypothesis testing/002 What is an hypothesis and how do you specify one__en.srt 23.3 KB
16 - Clustering and dimension-reduction/010 Principal components analysis (PCA)_en.srt 23.3 KB
10 - The t-test family/009 Code_ Signed-rank test_en.vtt 23.0 KB
12 - Correlation/018 Code_ Kendall correlation_en.vtt 23.0 KB
05 - Visualizing data/002 Code_ bar plots_en.vtt 22.7 KB
13 - Analysis of Variance (ANOVA)/001 ANOVA intro, part1_en.vtt 22.6 KB
16 - Clustering and dimension-reduction/011 Code_ PCA_en.vtt 22.6 KB
06 - Descriptive statistics/011 Measures of dispersion (variance, standard deviation)_en.vtt 22.6 KB
18 - A real-world data journey/35855734-state-divorce-rates-90-95-99-19.xlsx 22.5 KB
14 - Regression/011 Code_ polynomial modeling_en.srt 22.4 KB
13 - Analysis of Variance (ANOVA)/003 Sum of squares_en.vtt 22.3 KB
09 - Hypothesis testing/004 P-values_ definition, tails, and misinterpretations_en.vtt 22.2 KB
09 - Hypothesis testing/007 Type 1 and Type 2 errors_en.srt 22.2 KB
11 - Confidence intervals on parameters/003 Code_ compute confidence intervals by formula_en.vtt 22.1 KB
08 - Probability theory/004 Code_ compute probabilities_en.srt 22.0 KB
13 - Analysis of Variance (ANOVA)/008 Code_ One-way ANOVA (independent samples)_en.vtt 21.9 KB
17 - Signal detection theory/003 Code_ d-prime_en.srt 21.9 KB
14 - Regression/013 Logistic regression_en.vtt 21.8 KB
14 - Regression/015 Under- and over-fitting_en.vtt 21.7 KB
16 - Clustering and dimension-reduction/005 Clustering via dbscan_en.srt 21.7 KB
11 - Confidence intervals on parameters/005 Code_ bootstrapping confidence intervals_en.srt 21.7 KB
07 - Data normalizations and outliers/007 What are outliers and why are they dangerous__en.srt 21.5 KB
13 - Analysis of Variance (ANOVA)/011 Code_ Two-way mixed ANOVA_en.srt 21.4 KB
16 - Clustering and dimension-reduction/001 K-means clustering_en.srt 21.0 KB
04 - What are (is_) data_/003 Types of data_ categorical, numerical, etc_en.srt 20.9 KB
09 - Hypothesis testing/001 IVs, DVs, models, and other stats lingo_en.vtt 20.9 KB
05 - Visualizing data/007 Code_ histograms_en.vtt 20.8 KB
12 - Correlation/002 Covariance and correlation_ formulas_en.srt 20.8 KB
13 - Analysis of Variance (ANOVA)/007 One-way ANOVA example_en.srt 20.6 KB
18 - A real-world data journey/003 MATLAB_ Import and clean the marriage data_en.vtt 20.5 KB
14 - Regression/003 Evaluating regression models_ R2 and F_en.vtt 20.5 KB
08 - Probability theory/009 Cumulative distribution functions_en.srt 20.4 KB
08 - Probability theory/023 Code_ the CLT in action_en.vtt 20.3 KB
16 - Clustering and dimension-reduction/010 Principal components analysis (PCA)_en.vtt 20.3 KB
06 - Descriptive statistics/014 Code_ IQR_en.vtt 20.1 KB
06 - Descriptive statistics/009 Code_ computing central tendency_en.srt 20.1 KB
06 - Descriptive statistics/016 Code_ QQ plots_en.vtt 20.1 KB
12 - Correlation/004 Code_ Simulate data with specified correlation_en.srt 20.0 KB
07 - Data normalizations and outliers/017 Nonlinear data transformations_en.srt 19.8 KB
09 - Hypothesis testing/002 What is an hypothesis and how do you specify one__en.vtt 19.7 KB
14 - Regression/004 Simple regression_en.srt 19.7 KB
05 - Visualizing data/010 Code_ pie charts_en.srt 19.4 KB
14 - Regression/011 Code_ polynomial modeling_en.vtt 19.3 KB
07 - Data normalizations and outliers/003 Code_ z-score_en.srt 19.3 KB
17 - Signal detection theory/002 d-prime_en.srt 19.2 KB
14 - Regression/007 Multiple regression_en.srt 19.1 KB
09 - Hypothesis testing/007 Type 1 and Type 2 errors_en.vtt 19.0 KB
06 - Descriptive statistics/007 Measures of central tendency (mean)_en.srt 19.0 KB
10 - The t-test family/005 Two-samples t-test_en.srt 19.0 KB
10 - The t-test family/001 Purpose and interpretation of the t-test_en.srt 18.9 KB
08 - Probability theory/004 Code_ compute probabilities_en.vtt 18.9 KB
13 - Analysis of Variance (ANOVA)/005 The omnibus F-test and post-hoc comparisons_en.srt 18.8 KB
08 - Probability theory/017 Conditional probability_en.srt 18.8 KB
17 - Signal detection theory/003 Code_ d-prime_en.vtt 18.8 KB
16 - Clustering and dimension-reduction/005 Clustering via dbscan_en.vtt 18.7 KB
18 - A real-world data journey/008 Python_ Import the divorce data_en.srt 18.5 KB
07 - Data normalizations and outliers/007 What are outliers and why are they dangerous__en.vtt 18.5 KB
16 - Clustering and dimension-reduction/014 Code_ ICA_en.srt 18.4 KB
08 - Probability theory/007 Probability mass vs. density_en.srt 18.4 KB
11 - Confidence intervals on parameters/005 Code_ bootstrapping confidence intervals_en.vtt 18.4 KB
13 - Analysis of Variance (ANOVA)/009 Code_ One-way repeated-measures ANOVA_en.srt 18.4 KB
13 - Analysis of Variance (ANOVA)/011 Code_ Two-way mixed ANOVA_en.vtt 18.4 KB
14 - Regression/008 Standardizing regression coefficients_en.srt 18.3 KB
16 - Clustering and dimension-reduction/009 Code_ KNN_en.srt 18.2 KB
06 - Descriptive statistics/008 Measures of central tendency (median, mode)_en.srt 18.2 KB
04 - What are (is_) data_/003 Types of data_ categorical, numerical, etc_en.vtt 18.1 KB
16 - Clustering and dimension-reduction/001 K-means clustering_en.vtt 18.1 KB
08 - Probability theory/001 What is probability__en.srt 17.9 KB
12 - Correlation/002 Covariance and correlation_ formulas_en.vtt 17.9 KB
06 - Descriptive statistics/019 Code_ Histogram bins_en.srt 17.9 KB
08 - Probability theory/009 Cumulative distribution functions_en.vtt 17.7 KB
13 - Analysis of Variance (ANOVA)/007 One-way ANOVA example_en.vtt 17.7 KB
12 - Correlation/018 Code_ Kendall correlation_en.srt 17.6 KB
06 - Descriptive statistics/009 Code_ computing central tendency_en.vtt 17.4 KB
07 - Data normalizations and outliers/017 Nonlinear data transformations_en.vtt 17.4 KB
12 - Correlation/004 Code_ Simulate data with specified correlation_en.vtt 17.3 KB
14 - Regression/017 Comparing _nested_ models_en.srt 17.3 KB
16 - Clustering and dimension-reduction/013 Independent components analysis (ICA)_en.srt 17.3 KB
04 - What are (is_) data_/005 Sample vs. population data_en.srt 17.2 KB
05 - Visualizing data/001 Bar plots_en.srt 17.0 KB
09 - Hypothesis testing/012 Statistical significance vs. classification accuracy_en.srt 17.0 KB
14 - Regression/004 Simple regression_en.vtt 17.0 KB
06 - Descriptive statistics/003 Data distributions_en.srt 16.8 KB
05 - Visualizing data/010 Code_ pie charts_en.vtt 16.7 KB
07 - Data normalizations and outliers/003 Code_ z-score_en.vtt 16.6 KB
15 - Statistical power and sample sizes/002 Estimating statistical power and sample size_en.srt 16.6 KB
14 - Regression/007 Multiple regression_en.vtt 16.5 KB
17 - Signal detection theory/002 d-prime_en.vtt 16.5 KB
09 - Hypothesis testing/011 Cross-validation_en.srt 16.4 KB
10 - The t-test family/001 Purpose and interpretation of the t-test_en.vtt 16.4 KB
10 - The t-test family/005 Two-samples t-test_en.vtt 16.4 KB
10 - The t-test family/012 Permutation testing for t-test significance_en.srt 16.4 KB
06 - Descriptive statistics/007 Measures of central tendency (mean)_en.vtt 16.3 KB
07 - Data normalizations and outliers/015 Code_ Data trimming to remove outliers_en.srt 16.3 KB
13 - Analysis of Variance (ANOVA)/005 The omnibus F-test and post-hoc comparisons_en.vtt 16.2 KB
08 - Probability theory/017 Conditional probability_en.vtt 16.1 KB
18 - A real-world data journey/008 Python_ Import the divorce data_en.vtt 16.1 KB
18 - A real-world data journey/009 Python_ Inferential statistics_en.srt 16.1 KB
13 - Analysis of Variance (ANOVA)/010 Two-way ANOVA example_en.srt 16.1 KB
08 - Probability theory/008 Code_ compute probability mass functions_en.srt 16.0 KB
09 - Hypothesis testing/006 Degrees of freedom_en.vtt 16.0 KB
08 - Probability theory/007 Probability mass vs. density_en.vtt 16.0 KB
16 - Clustering and dimension-reduction/014 Code_ ICA_en.vtt 15.9 KB
13 - Analysis of Variance (ANOVA)/009 Code_ One-way repeated-measures ANOVA_en.vtt 15.9 KB
05 - Visualizing data/006 Histograms_en.srt 15.8 KB
14 - Regression/008 Standardizing regression coefficients_en.vtt 15.7 KB
06 - Descriptive statistics/008 Measures of central tendency (median, mode)_en.vtt 15.7 KB
08 - Probability theory/022 The Central Limit Theorem_en.srt 15.6 KB
06 - Descriptive statistics/023 Shannon entropy_en.srt 15.5 KB
16 - Clustering and dimension-reduction/009 Code_ KNN_en.vtt 15.5 KB
08 - Probability theory/001 What is probability__en.vtt 15.5 KB
06 - Descriptive statistics/021 Code_ violin plots_en.srt 15.4 KB
12 - Correlation/009 Partial correlation_en.srt 15.4 KB
06 - Descriptive statistics/019 Code_ Histogram bins_en.vtt 15.4 KB
08 - Probability theory/016 Expected value_en.srt 15.4 KB
18 - A real-world data journey/006 MATLAB_ Inferential statistics_en.srt 15.3 KB
05 - Visualizing data/001 Bar plots_en.vtt 15.3 KB
12 - Correlation/017 Kendall's correlation for ordinal data_en.srt 15.2 KB
08 - Probability theory/003 Computing probabilities_en.srt 15.2 KB
14 - Regression/017 Comparing _nested_ models_en.vtt 15.1 KB
16 - Clustering and dimension-reduction/013 Independent components analysis (ICA)_en.vtt 15.1 KB
04 - What are (is_) data_/005 Sample vs. population data_en.vtt 14.9 KB
09 - Hypothesis testing/012 Statistical significance vs. classification accuracy_en.vtt 14.7 KB
09 - Hypothesis testing/003 Sample distributions under null and alternative hypotheses_en.srt 14.7 KB
06 - Descriptive statistics/003 Data distributions_en.vtt 14.5 KB
08 - Probability theory/010 Code_ cdfs and pdfs_en.srt 14.5 KB
08 - Probability theory/020 The Law of Large Numbers_en.srt 14.4 KB
07 - Data normalizations and outliers/012 Multivariate outlier detection_en.srt 14.4 KB
15 - Statistical power and sample sizes/002 Estimating statistical power and sample size_en.vtt 14.3 KB
15 - Statistical power and sample sizes/001 What is statistical power and why is it important__en.srt 14.3 KB
14 - Regression/002 Least-squares solution to the GLM_en.srt 14.3 KB
09 - Hypothesis testing/011 Cross-validation_en.vtt 14.3 KB
06 - Descriptive statistics/018 Histograms part 2_ Number of bins_en.srt 14.3 KB
07 - Data normalizations and outliers/002 Z-score standardization_en.srt 14.3 KB
10 - The t-test family/012 Permutation testing for t-test significance_en.vtt 14.2 KB
14 - Regression/014 Code_ Logistic regression_en.srt 14.2 KB
07 - Data normalizations and outliers/008 Removing outliers_ z-score method_en.srt 14.1 KB
08 - Probability theory/002 Probability vs. proportion_en.srt 14.1 KB
07 - Data normalizations and outliers/015 Code_ Data trimming to remove outliers_en.vtt 14.0 KB
18 - A real-world data journey/009 Python_ Inferential statistics_en.vtt 14.0 KB
08 - Probability theory/008 Code_ compute probability mass functions_en.vtt 14.0 KB
13 - Analysis of Variance (ANOVA)/010 Two-way ANOVA example_en.vtt 14.0 KB
05 - Visualizing data/006 Histograms_en.vtt 13.7 KB
12 - Correlation/005 Correlation matrix_en.srt 13.6 KB
08 - Probability theory/022 The Central Limit Theorem_en.vtt 13.5 KB
06 - Descriptive statistics/023 Shannon entropy_en.vtt 13.5 KB
14 - Regression/005 Code_ simple regression_en.srt 13.4 KB
12 - Correlation/009 Partial correlation_en.vtt 13.4 KB
18 - A real-world data journey/006 MATLAB_ Inferential statistics_en.vtt 13.3 KB
01 - Introductions/003 Statistics guessing game__en.srt 13.3 KB
08 - Probability theory/016 Expected value_en.vtt 13.2 KB
06 - Descriptive statistics/021 Code_ violin plots_en.vtt 13.2 KB
12 - Correlation/017 Kendall's correlation for ordinal data_en.vtt 13.1 KB
11 - Confidence intervals on parameters/001 What are confidence intervals and why do we need them__en.srt 13.1 KB
02 - Math prerequisites/007 The logistic function_en.srt 13.1 KB
04 - What are (is_) data_/004 Code_ representing types of data on computers_en.srt 13.1 KB
08 - Probability theory/003 Computing probabilities_en.vtt 13.1 KB
06 - Descriptive statistics/017 Statistical _moments__en.srt 13.1 KB
08 - Probability theory/014 Sampling variability, noise, and other annoyances_en.srt 13.1 KB
09 - Hypothesis testing/008 Parametric vs. non-parametric tests_en.srt 12.9 KB
11 - Confidence intervals on parameters/004 Confidence intervals via bootstrapping (resampling)_en.srt 12.8 KB
09 - Hypothesis testing/003 Sample distributions under null and alternative hypotheses_en.vtt 12.8 KB
07 - Data normalizations and outliers/013 Code_ Euclidean distance for outlier removal_en.srt 12.8 KB
05 - Visualizing data/004 Code_ box plots_en.srt 12.8 KB
08 - Probability theory/010 Code_ cdfs and pdfs_en.vtt 12.6 KB
07 - Data normalizations and outliers/005 Code_ min-max scaling_en.srt 12.6 KB
15 - Statistical power and sample sizes/001 What is statistical power and why is it important__en.vtt 12.5 KB
09 - Hypothesis testing/009 Multiple comparisons and Bonferroni correction_en.srt 12.5 KB
05 - Visualizing data/012 Linear vs. logarithmic axis scaling_en.srt 12.5 KB
08 - Probability theory/020 The Law of Large Numbers_en.vtt 12.5 KB
06 - Descriptive statistics/018 Histograms part 2_ Number of bins_en.vtt 12.4 KB
14 - Regression/002 Least-squares solution to the GLM_en.vtt 12.3 KB
18 - A real-world data journey/004 MATLAB_ Import the divorce data_en.srt 12.3 KB
07 - Data normalizations and outliers/002 Z-score standardization_en.vtt 12.3 KB
07 - Data normalizations and outliers/012 Multivariate outlier detection_en.vtt 12.3 KB
17 - Signal detection theory/004 Response bias_en.srt 12.3 KB
14 - Regression/010 Polynomial regression models_en.srt 12.2 KB
07 - Data normalizations and outliers/008 Removing outliers_ z-score method_en.vtt 12.2 KB
14 - Regression/014 Code_ Logistic regression_en.vtt 12.1 KB
08 - Probability theory/002 Probability vs. proportion_en.vtt 12.1 KB
12 - Correlation/005 Correlation matrix_en.vtt 11.7 KB
17 - Signal detection theory/008 Code_ ROC curves_en.srt 11.7 KB
10 - The t-test family/002 One-sample t-test_en.srt 11.6 KB
14 - Regression/005 Code_ simple regression_en.vtt 11.5 KB
01 - Introductions/003 Statistics guessing game__en.vtt 11.5 KB
06 - Descriptive statistics/002 Accuracy, precision, resolution_en.srt 11.4 KB
08 - Probability theory/014 Sampling variability, noise, and other annoyances_en.vtt 11.4 KB
11 - Confidence intervals on parameters/001 What are confidence intervals and why do we need them__en.vtt 11.3 KB
09 - Hypothesis testing/008 Parametric vs. non-parametric tests_en.vtt 11.3 KB
02 - Math prerequisites/007 The logistic function_en.vtt 11.3 KB
11 - Confidence intervals on parameters/004 Confidence intervals via bootstrapping (resampling)_en.vtt 11.2 KB
06 - Descriptive statistics/017 Statistical _moments__en.vtt 11.2 KB
04 - What are (is_) data_/004 Code_ representing types of data on computers_en.vtt 11.2 KB
12 - Correlation/014 Code_ Spearman correlation and Fisher-Z_en.srt 11.1 KB
07 - Data normalizations and outliers/013 Code_ Euclidean distance for outlier removal_en.vtt 11.0 KB
17 - Signal detection theory/007 Receiver operating characteristics (ROC)_en.srt 11.0 KB
05 - Visualizing data/004 Code_ box plots_en.vtt 10.9 KB
05 - Visualizing data/013 Code_ line plots_en.srt 10.9 KB
09 - Hypothesis testing/009 Multiple comparisons and Bonferroni correction_en.vtt 10.8 KB
05 - Visualizing data/012 Linear vs. logarithmic axis scaling_en.vtt 10.8 KB
07 - Data normalizations and outliers/005 Code_ min-max scaling_en.vtt 10.7 KB
12 - Correlation/012 Nonparametric correlation_ Spearman rank_en.srt 10.7 KB
14 - Regression/010 Polynomial regression models_en.vtt 10.6 KB
18 - A real-world data journey/004 MATLAB_ Import the divorce data_en.vtt 10.6 KB
17 - Signal detection theory/004 Response bias_en.vtt 10.6 KB
13 - Analysis of Variance (ANOVA)/004 The F-test and the ANOVA table_en.srt 10.5 KB
10 - The t-test family/008 Wilcoxon signed-rank (nonparametric t-test)_en.srt 10.4 KB
04 - What are (is_) data_/007 The ethics of making up data_en.srt 10.3 KB
06 - Descriptive statistics/015 QQ plots_en.srt 10.2 KB
17 - Signal detection theory/008 Code_ ROC curves_en.vtt 10.1 KB
10 - The t-test family/002 One-sample t-test_en.vtt 10.0 KB
09 - Hypothesis testing/010 Statistical vs. theoretical vs. clinical significance_en.srt 10.0 KB
08 - Probability theory/019 Tree diagrams for conditional probabilities_en.srt 9.9 KB
12 - Correlation/011 The problem with Pearson_en.srt 9.9 KB
12 - Correlation/013 Fisher-Z transformation for correlations_en.srt 9.9 KB
06 - Descriptive statistics/002 Accuracy, precision, resolution_en.vtt 9.8 KB
12 - Correlation/014 Code_ Spearman correlation and Fisher-Z_en.vtt 9.6 KB
14 - Regression/018 What to do about missing data_en.srt 9.6 KB
17 - Signal detection theory/007 Receiver operating characteristics (ROC)_en.vtt 9.6 KB
02 - Math prerequisites/008 Rank and tied-rank_en.srt 9.5 KB
11 - Confidence intervals on parameters/002 Computing confidence intervals via formula_en.srt 9.4 KB
05 - Visualizing data/013 Code_ line plots_en.vtt 9.4 KB
12 - Correlation/012 Nonparametric correlation_ Spearman rank_en.vtt 9.3 KB
18 - A real-world data journey/005 MATLAB_ More data visualizations_en.srt 9.3 KB
13 - Analysis of Variance (ANOVA)/004 The F-test and the ANOVA table_en.vtt 9.2 KB
10 - The t-test family/008 Wilcoxon signed-rank (nonparametric t-test)_en.vtt 9.1 KB
11 - Confidence intervals on parameters/007 Misconceptions about confidence intervals_en.srt 9.1 KB
09 - Hypothesis testing/005 P-z combinations that you should memorize_en.srt 9.0 KB
16 - Clustering and dimension-reduction/008 K-nearest neighbor classification_en.srt 9.0 KB
04 - What are (is_) data_/007 The ethics of making up data_en.vtt 8.9 KB
06 - Descriptive statistics/015 QQ plots_en.vtt 8.9 KB
10 - The t-test family/010 Mann-Whitney U test (nonparametric t-test)_en.srt 8.8 KB
18 - A real-world data journey/010 Take-home messages_en.srt 8.7 KB
02 - Math prerequisites/003 Scientific notation_en.srt 8.7 KB
17 - Signal detection theory/001 The two perspectives of the world_en.srt 8.7 KB
12 - Correlation/011 The problem with Pearson_en.vtt 8.7 KB
09 - Hypothesis testing/010 Statistical vs. theoretical vs. clinical significance_en.vtt 8.6 KB
12 - Correlation/013 Fisher-Z transformation for correlations_en.vtt 8.6 KB
05 - Visualizing data/011 When to use lines instead of bars_en.srt 8.6 KB
08 - Probability theory/019 Tree diagrams for conditional probabilities_en.vtt 8.6 KB
07 - Data normalizations and outliers/014 Removing outliers by data trimming_en.srt 8.5 KB
05 - Visualizing data/009 Pie charts_en.srt 8.5 KB
04 - What are (is_) data_/002 Where do data come from and what do they mean__en.srt 8.4 KB
14 - Regression/018 What to do about missing data_en.vtt 8.4 KB
02 - Math prerequisites/008 Rank and tied-rank_en.vtt 8.2 KB
11 - Confidence intervals on parameters/002 Computing confidence intervals via formula_en.vtt 8.2 KB
18 - A real-world data journey/005 MATLAB_ More data visualizations_en.vtt 8.2 KB
01 - Introductions/004 Using the Q&A forum_en.srt 8.1 KB
02 - Math prerequisites/006 Natural exponent and logarithm_en.srt 8.1 KB
11 - Confidence intervals on parameters/007 Misconceptions about confidence intervals_en.vtt 7.9 KB
09 - Hypothesis testing/005 P-z combinations that you should memorize_en.vtt 7.9 KB
16 - Clustering and dimension-reduction/008 K-nearest neighbor classification_en.vtt 7.8 KB
05 - Visualizing data/003 Box-and-whisker plots_en.srt 7.8 KB
10 - The t-test family/011 Code_ Mann-Whitney U test_en.srt 7.7 KB
10 - The t-test family/014 _Unsupervised learning__ How many permutations__en.srt 7.7 KB
04 - What are (is_) data_/006 Samples, case reports, and anecdotes_en.srt 7.7 KB
10 - The t-test family/010 Mann-Whitney U test (nonparametric t-test)_en.vtt 7.7 KB
06 - Descriptive statistics/006 The beauty and simplicity of Normal_en.srt 7.6 KB
18 - A real-world data journey/010 Take-home messages_en.vtt 7.6 KB
17 - Signal detection theory/001 The two perspectives of the world_en.vtt 7.5 KB
12 - Correlation/021 Cosine similarity_en.srt 7.5 KB
02 - Math prerequisites/003 Scientific notation_en.vtt 7.5 KB
05 - Visualizing data/011 When to use lines instead of bars_en.vtt 7.5 KB
07 - Data normalizations and outliers/014 Removing outliers by data trimming_en.vtt 7.4 KB
05 - Visualizing data/009 Pie charts_en.vtt 7.3 KB
04 - What are (is_) data_/002 Where do data come from and what do they mean__en.vtt 7.3 KB
07 - Data normalizations and outliers/004 Min-max scaling_en.srt 7.2 KB
01 - Introductions/004 Using the Q&A forum_en.vtt 7.1 KB
06 - Descriptive statistics/013 Interquartile range (IQR)_en.srt 7.0 KB
02 - Math prerequisites/006 Natural exponent and logarithm_en.vtt 7.0 KB
12 - Correlation/020 The subgroups correlation paradox_en.srt 7.0 KB
08 - Probability theory/005 Probability and odds_en.srt 6.9 KB
10 - The t-test family/007 _Unsupervised learning__ Importance of N for t-test_en.srt 6.9 KB
15 - Statistical power and sample sizes/003 Compute power and sample size using G_Power_en.srt 6.8 KB
05 - Visualizing data/003 Box-and-whisker plots_en.vtt 6.8 KB
04 - What are (is_) data_/006 Samples, case reports, and anecdotes_en.vtt 6.7 KB
10 - The t-test family/014 _Unsupervised learning__ How many permutations__en.vtt 6.7 KB
06 - Descriptive statistics/006 The beauty and simplicity of Normal_en.vtt 6.7 KB
10 - The t-test family/011 Code_ Mann-Whitney U test_en.vtt 6.7 KB
12 - Correlation/021 Cosine similarity_en.vtt 6.5 KB
06 - Descriptive statistics/001 Descriptive vs. inferential statistics_en.srt 6.4 KB
17 - Signal detection theory/005 Code_ Response bias_en.srt 6.3 KB
07 - Data normalizations and outliers/016 Non-parametric solutions to outliers_en.srt 6.3 KB
07 - Data normalizations and outliers/004 Min-max scaling_en.vtt 6.3 KB
18 - A real-world data journey/002 Introduction_en.srt 6.2 KB
12 - Correlation/020 The subgroups correlation paradox_en.vtt 6.1 KB
06 - Descriptive statistics/013 Interquartile range (IQR)_en.vtt 6.1 KB
01 - Introductions/001 [Important] Getting the most out of this course_en.srt 6.1 KB
08 - Probability theory/005 Probability and odds_en.vtt 6.0 KB
02 - Math prerequisites/004 Summation notation_en.srt 6.0 KB
10 - The t-test family/007 _Unsupervised learning__ Importance of N for t-test_en.vtt 5.9 KB
01 - Introductions/002 About using MATLAB or Python_en.srt 5.9 KB
07 - Data normalizations and outliers/009 The modified z-score method_en.srt 5.9 KB
12 - Correlation/008 _Unsupervised learning__ correlation to covariance matrix_en.srt 5.8 KB
15 - Statistical power and sample sizes/003 Compute power and sample size using G_Power_en.vtt 5.8 KB
07 - Data normalizations and outliers/001 Garbage in, garbage out (GIGO)_en.srt 5.7 KB
02 - Math prerequisites/002 Arithmetic and exponents_en.srt 5.6 KB
06 - Descriptive statistics/001 Descriptive vs. inferential statistics_en.vtt 5.6 KB
07 - Data normalizations and outliers/016 Non-parametric solutions to outliers_en.vtt 5.6 KB
17 - Signal detection theory/005 Code_ Response bias_en.vtt 5.5 KB
18 - A real-world data journey/002 Introduction_en.vtt 5.4 KB
03 - IMPORTANT_ Download course materials/001 Download materials for the entire course__en.srt 5.4 KB
01 - Introductions/001 [Important] Getting the most out of this course_en.vtt 5.4 KB
02 - Math prerequisites/004 Summation notation_en.vtt 5.2 KB
01 - Introductions/002 About using MATLAB or Python_en.vtt 5.2 KB
07 - Data normalizations and outliers/009 The modified z-score method_en.vtt 5.1 KB
12 - Correlation/008 _Unsupervised learning__ correlation to covariance matrix_en.vtt 5.1 KB
07 - Data normalizations and outliers/001 Garbage in, garbage out (GIGO)_en.vtt 5.0 KB
06 - Descriptive statistics/020 Violin plots_en.srt 5.0 KB
02 - Math prerequisites/002 Arithmetic and exponents_en.vtt 4.9 KB
03 - IMPORTANT_ Download course materials/001 Download materials for the entire course__en.vtt 4.8 KB
16 - Clustering and dimension-reduction/007 _Unsupervised learning__ dbscan vs. k-means_en.srt 4.4 KB
06 - Descriptive statistics/010 _Unsupervised learning__ central tendencies with outliers_en.srt 4.3 KB
06 - Descriptive statistics/020 Violin plots_en.vtt 4.3 KB
02 - Math prerequisites/005 Absolute value_en.srt 4.2 KB
02 - Math prerequisites/001 Should you memorize statistical formulas__en.srt 4.2 KB
07 - Data normalizations and outliers/018 An outlier lecture on personal accountability_en.srt 4.1 KB
10 - The t-test family/004 _Unsupervised learning__ The role of variance_en.srt 4.1 KB
12 - Correlation/007 _Unsupervised learning__ average correlation matrices_en.srt 4.1 KB
16 - Clustering and dimension-reduction/007 _Unsupervised learning__ dbscan vs. k-means_en.vtt 3.9 KB
06 - Descriptive statistics/022 _Unsupervised learning__ asymmetric violin plots_en.srt 3.8 KB
07 - Data normalizations and outliers/011 _Unsupervised learning__ z vs. modified-z_en.srt 3.8 KB
08 - Probability theory/013 Monte Carlo sampling_en.srt 3.8 KB
06 - Descriptive statistics/010 _Unsupervised learning__ central tendencies with outliers_en.vtt 3.8 KB
05 - Visualizing data/005 _Unsupervised learning__ Boxplots of normal and uniform noise_en.srt 3.7 KB
01 - Introductions/25299297-stats-intro-GuessTheTest.zip 3.7 KB
02 - Math prerequisites/001 Should you memorize statistical formulas__en.vtt 3.7 KB
02 - Math prerequisites/005 Absolute value_en.vtt 3.7 KB
07 - Data normalizations and outliers/018 An outlier lecture on personal accountability_en.vtt 3.6 KB
19 - Bonus section/002 Bonus content.html 3.6 KB
07 - Data normalizations and outliers/006 _Unsupervised learning__ Invert the min-max scaling_en.srt 3.6 KB
10 - The t-test family/004 _Unsupervised learning__ The role of variance_en.vtt 3.6 KB
12 - Correlation/007 _Unsupervised learning__ average correlation matrices_en.vtt 3.6 KB
05 - Visualizing data/008 _Unsupervised learning__ Histogram proportion_en.srt 3.4 KB
07 - Data normalizations and outliers/011 _Unsupervised learning__ z vs. modified-z_en.vtt 3.4 KB
08 - Probability theory/013 Monte Carlo sampling_en.vtt 3.4 KB
08 - Probability theory/011 _Unsupervised learning__ cdf's for various distributions_en.srt 3.3 KB
12 - Correlation/016 _Unsupervised learning__ confidence interval on correlation_en.srt 3.3 KB
06 - Descriptive statistics/022 _Unsupervised learning__ asymmetric violin plots_en.vtt 3.3 KB
12 - Correlation/019 _Unsupervised learning__ Does Kendall vs. Pearson matter__en.srt 3.3 KB
05 - Visualizing data/005 _Unsupervised learning__ Boxplots of normal and uniform noise_en.vtt 3.3 KB
08 - Probability theory/024 _Unsupervised learning__ Averaging pairs of numbers_en.srt 3.2 KB
07 - Data normalizations and outliers/006 _Unsupervised learning__ Invert the min-max scaling_en.vtt 3.2 KB
08 - Probability theory/006 _Unsupervised learning__ probabilities of odds-space_en.srt 3.1 KB
01 - Introductions/005 (optional) Entering time-stamped notes in the Udemy video player_en.srt 3.1 KB
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 2.9 KB
08 - Probability theory/011 _Unsupervised learning__ cdf's for various distributions_en.vtt 2.9 KB
12 - Correlation/016 _Unsupervised learning__ confidence interval on correlation_en.vtt 2.9 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 2.7 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 2.6 KB
09 - Hypothesis testing/006 Degrees of freedom_en.srt 2.6 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 2.3 KB
04 - What are (is_) data_/001 Is _data_ singular or plural________en.srt 2.3 KB
16 - Clustering and dimension-reduction/012 _Unsupervised learning__ K-means on PC data_en.srt 2.2 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 2.1 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 2.0 KB
06 - Descriptive statistics/025 _Unsupervised learning__ entropy and number of bins_en.srt 2.0 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 1.9 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 1.6 KB
14 - Regression/006 _Unsupervised learning__ Compute R2 and F_en.srt 1.4 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 1010 bytes
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

[Tutorialsplanet.NET] Udemy - Master statistics & machine learning - intuition, math, code

File List

Download Torrent

Related Resources

Copyright Infringement