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磁力链接/BT种子名称
[Tutorialsplanet.NET] Udemy - Master statistics & machine learning - intuition, math, code
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文件列表
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
16 - Clustering and dimension-reduction/010 Principal components analysis (PCA)_en.vtt
20.7 kB
06 - Descriptive statistics/014 Code_ IQR_en.vtt
20.6 kB
06 - Descriptive statistics/009 Code_ computing central tendency_en.srt
20.6 kB
06 - Descriptive statistics/016 Code_ QQ plots_en.vtt
20.6 kB
12 - Correlation/004 Code_ Simulate data with specified correlation_en.srt
20.5 kB
07 - Data normalizations and outliers/017 Nonlinear data transformations_en.srt
20.3 kB
09 - Hypothesis testing/002 What is an hypothesis and how do you specify one__en.vtt
20.2 kB
14 - Regression/004 Simple regression_en.srt
20.2 kB
05 - Visualizing data/010 Code_ pie charts_en.srt
19.8 kB
14 - Regression/011 Code_ polynomial modeling_en.vtt
19.8 kB
07 - Data normalizations and outliers/003 Code_ z-score_en.srt
19.7 kB
17 - Signal detection theory/002 d-prime_en.srt
19.7 kB
14 - Regression/007 Multiple regression_en.srt
19.6 kB
09 - Hypothesis testing/007 Type 1 and Type 2 errors_en.vtt
19.5 kB
06 - Descriptive statistics/007 Measures of central tendency (mean)_en.srt
19.4 kB
10 - The t-test family/005 Two-samples t-test_en.srt
19.4 kB
10 - The t-test family/001 Purpose and interpretation of the t-test_en.srt
19.4 kB
08 - Probability theory/004 Code_ compute probabilities_en.vtt
19.3 kB
13 - Analysis of Variance (ANOVA)/005 The omnibus F-test and post-hoc comparisons_en.srt
19.3 kB
08 - Probability theory/017 Conditional probability_en.srt
19.3 kB
17 - Signal detection theory/003 Code_ d-prime_en.vtt
19.2 kB
16 - Clustering and dimension-reduction/005 Clustering via dbscan_en.vtt
19.1 kB
18 - A real-world data journey/008 Python_ Import the divorce data_en.srt
19.0 kB
07 - Data normalizations and outliers/007 What are outliers and why are they dangerous__en.vtt
19.0 kB
16 - Clustering and dimension-reduction/014 Code_ ICA_en.srt
18.9 kB
08 - Probability theory/007 Probability mass vs. density_en.srt
18.9 kB
11 - Confidence intervals on parameters/005 Code_ bootstrapping confidence intervals_en.vtt
18.9 kB
13 - Analysis of Variance (ANOVA)/009 Code_ One-way repeated-measures ANOVA_en.srt
18.8 kB
13 - Analysis of Variance (ANOVA)/011 Code_ Two-way mixed ANOVA_en.vtt
18.8 kB
14 - Regression/008 Standardizing regression coefficients_en.srt
18.8 kB
16 - Clustering and dimension-reduction/009 Code_ KNN_en.srt
18.6 kB
06 - Descriptive statistics/008 Measures of central tendency (median, mode)_en.srt
18.6 kB
04 - What are (is_) data_/003 Types of data_ categorical, numerical, etc_en.vtt
18.5 kB
16 - Clustering and dimension-reduction/001 K-means clustering_en.vtt
18.5 kB
08 - Probability theory/001 What is probability__en.srt
18.4 kB
12 - Correlation/002 Covariance and correlation_ formulas_en.vtt
18.3 kB
06 - Descriptive statistics/019 Code_ Histogram bins_en.srt
18.3 kB
08 - Probability theory/009 Cumulative distribution functions_en.vtt
18.2 kB
13 - Analysis of Variance (ANOVA)/007 One-way ANOVA example_en.vtt
18.1 kB
12 - Correlation/018 Code_ Kendall correlation_en.srt
18.0 kB
06 - Descriptive statistics/009 Code_ computing central tendency_en.vtt
17.8 kB
07 - Data normalizations and outliers/017 Nonlinear data transformations_en.vtt
17.8 kB
12 - Correlation/004 Code_ Simulate data with specified correlation_en.vtt
17.7 kB
14 - Regression/017 Comparing _nested_ models_en.srt
17.7 kB
16 - Clustering and dimension-reduction/013 Independent components analysis (ICA)_en.srt
17.7 kB
04 - What are (is_) data_/005 Sample vs. population data_en.srt
17.6 kB
05 - Visualizing data/001 Bar plots_en.srt
17.4 kB
09 - Hypothesis testing/012 Statistical significance vs. classification accuracy_en.srt
17.4 kB
14 - Regression/004 Simple regression_en.vtt
17.4 kB
06 - Descriptive statistics/003 Data distributions_en.srt
17.2 kB
05 - Visualizing data/010 Code_ pie charts_en.vtt
17.1 kB
07 - Data normalizations and outliers/003 Code_ z-score_en.vtt
17.0 kB
15 - Statistical power and sample sizes/002 Estimating statistical power and sample size_en.srt
17.0 kB
14 - Regression/007 Multiple regression_en.vtt
16.9 kB
17 - Signal detection theory/002 d-prime_en.vtt
16.8 kB
09 - Hypothesis testing/011 Cross-validation_en.srt
16.8 kB
10 - The t-test family/001 Purpose and interpretation of the t-test_en.vtt
16.8 kB
10 - The t-test family/005 Two-samples t-test_en.vtt
16.8 kB
10 - The t-test family/012 Permutation testing for t-test significance_en.srt
16.7 kB
06 - Descriptive statistics/007 Measures of central tendency (mean)_en.vtt
16.7 kB
07 - Data normalizations and outliers/015 Code_ Data trimming to remove outliers_en.srt
16.7 kB
13 - Analysis of Variance (ANOVA)/005 The omnibus F-test and post-hoc comparisons_en.vtt
16.6 kB
08 - Probability theory/017 Conditional probability_en.vtt
16.5 kB
18 - A real-world data journey/008 Python_ Import the divorce data_en.vtt
16.5 kB
18 - A real-world data journey/009 Python_ Inferential statistics_en.srt
16.5 kB
13 - Analysis of Variance (ANOVA)/010 Two-way ANOVA example_en.srt
16.5 kB
08 - Probability theory/008 Code_ compute probability mass functions_en.srt
16.4 kB
09 - Hypothesis testing/006 Degrees of freedom_en.vtt
16.4 kB
08 - Probability theory/007 Probability mass vs. density_en.vtt
16.3 kB
16 - Clustering and dimension-reduction/014 Code_ ICA_en.vtt
16.3 kB
13 - Analysis of Variance (ANOVA)/009 Code_ One-way repeated-measures ANOVA_en.vtt
16.3 kB
05 - Visualizing data/006 Histograms_en.srt
16.2 kB
14 - Regression/008 Standardizing regression coefficients_en.vtt
16.1 kB
06 - Descriptive statistics/008 Measures of central tendency (median, mode)_en.vtt
16.1 kB
08 - Probability theory/022 The Central Limit Theorem_en.srt
15.9 kB
06 - Descriptive statistics/023 Shannon entropy_en.srt
15.9 kB
16 - Clustering and dimension-reduction/009 Code_ KNN_en.vtt
15.9 kB
08 - Probability theory/001 What is probability__en.vtt
15.9 kB
06 - Descriptive statistics/021 Code_ violin plots_en.srt
15.8 kB
12 - Correlation/009 Partial correlation_en.srt
15.8 kB
06 - Descriptive statistics/019 Code_ Histogram bins_en.vtt
15.8 kB
08 - Probability theory/016 Expected value_en.srt
15.7 kB
18 - A real-world data journey/006 MATLAB_ Inferential statistics_en.srt
15.7 kB
05 - Visualizing data/001 Bar plots_en.vtt
15.6 kB
12 - Correlation/017 Kendall's correlation for ordinal data_en.srt
15.6 kB
08 - Probability theory/003 Computing probabilities_en.srt
15.5 kB
14 - Regression/017 Comparing _nested_ models_en.vtt
15.5 kB
16 - Clustering and dimension-reduction/013 Independent components analysis (ICA)_en.vtt
15.4 kB
04 - What are (is_) data_/005 Sample vs. population data_en.vtt
15.3 kB
09 - Hypothesis testing/012 Statistical significance vs. classification accuracy_en.vtt
15.0 kB
09 - Hypothesis testing/003 Sample distributions under null and alternative hypotheses_en.srt
15.0 kB
06 - Descriptive statistics/003 Data distributions_en.vtt
14.9 kB
08 - Probability theory/010 Code_ cdfs and pdfs_en.srt
14.8 kB
08 - Probability theory/020 The Law of Large Numbers_en.srt
14.8 kB
07 - Data normalizations and outliers/012 Multivariate outlier detection_en.srt
14.7 kB
15 - Statistical power and sample sizes/002 Estimating statistical power and sample size_en.vtt
14.7 kB
15 - Statistical power and sample sizes/001 What is statistical power and why is it important__en.srt
14.7 kB
14 - Regression/002 Least-squares solution to the GLM_en.srt
14.7 kB
09 - Hypothesis testing/011 Cross-validation_en.vtt
14.7 kB
06 - Descriptive statistics/018 Histograms part 2_ Number of bins_en.srt
14.7 kB
07 - Data normalizations and outliers/002 Z-score standardization_en.srt
14.6 kB
10 - The t-test family/012 Permutation testing for t-test significance_en.vtt
14.5 kB
14 - Regression/014 Code_ Logistic regression_en.srt
14.5 kB
07 - Data normalizations and outliers/008 Removing outliers_ z-score method_en.srt
14.5 kB
08 - Probability theory/002 Probability vs. proportion_en.srt
14.5 kB
07 - Data normalizations and outliers/015 Code_ Data trimming to remove outliers_en.vtt
14.4 kB
18 - A real-world data journey/009 Python_ Inferential statistics_en.vtt
14.4 kB
08 - Probability theory/008 Code_ compute probability mass functions_en.vtt
14.4 kB
13 - Analysis of Variance (ANOVA)/010 Two-way ANOVA example_en.vtt
14.3 kB
05 - Visualizing data/006 Histograms_en.vtt
14.0 kB
12 - Correlation/005 Correlation matrix_en.srt
13.9 kB
08 - Probability theory/022 The Central Limit Theorem_en.vtt
13.8 kB
06 - Descriptive statistics/023 Shannon entropy_en.vtt
13.8 kB
14 - Regression/005 Code_ simple regression_en.srt
13.7 kB
12 - Correlation/009 Partial correlation_en.vtt
13.7 kB
18 - A real-world data journey/006 MATLAB_ Inferential statistics_en.vtt
13.7 kB
01 - Introductions/003 Statistics guessing game__en.srt
13.6 kB
08 - Probability theory/016 Expected value_en.vtt
13.5 kB
06 - Descriptive statistics/021 Code_ violin plots_en.vtt
13.5 kB
12 - Correlation/017 Kendall's correlation for ordinal data_en.vtt
13.4 kB
11 - Confidence intervals on parameters/001 What are confidence intervals and why do we need them__en.srt
13.4 kB
02 - Math prerequisites/007 The logistic function_en.srt
13.4 kB
04 - What are (is_) data_/004 Code_ representing types of data on computers_en.srt
13.4 kB
08 - Probability theory/003 Computing probabilities_en.vtt
13.4 kB
06 - Descriptive statistics/017 Statistical _moments__en.srt
13.4 kB
08 - Probability theory/014 Sampling variability, noise, and other annoyances_en.srt
13.4 kB
09 - Hypothesis testing/008 Parametric vs. non-parametric tests_en.srt
13.2 kB
11 - Confidence intervals on parameters/004 Confidence intervals via bootstrapping (resampling)_en.srt
13.1 kB
09 - Hypothesis testing/003 Sample distributions under null and alternative hypotheses_en.vtt
13.1 kB
07 - Data normalizations and outliers/013 Code_ Euclidean distance for outlier removal_en.srt
13.1 kB
05 - Visualizing data/004 Code_ box plots_en.srt
13.1 kB
08 - Probability theory/010 Code_ cdfs and pdfs_en.vtt
12.9 kB
07 - Data normalizations and outliers/005 Code_ min-max scaling_en.srt
12.9 kB
15 - Statistical power and sample sizes/001 What is statistical power and why is it important__en.vtt
12.8 kB
09 - Hypothesis testing/009 Multiple comparisons and Bonferroni correction_en.srt
12.8 kB
05 - Visualizing data/012 Linear vs. logarithmic axis scaling_en.srt
12.8 kB
08 - Probability theory/020 The Law of Large Numbers_en.vtt
12.8 kB
06 - Descriptive statistics/018 Histograms part 2_ Number of bins_en.vtt
12.7 kB
14 - Regression/002 Least-squares solution to the GLM_en.vtt
12.6 kB
18 - A real-world data journey/004 MATLAB_ Import the divorce data_en.srt
12.6 kB
07 - Data normalizations and outliers/002 Z-score standardization_en.vtt
12.6 kB
07 - Data normalizations and outliers/012 Multivariate outlier detection_en.vtt
12.6 kB
17 - Signal detection theory/004 Response bias_en.srt
12.5 kB
14 - Regression/010 Polynomial regression models_en.srt
12.5 kB
07 - Data normalizations and outliers/008 Removing outliers_ z-score method_en.vtt
12.5 kB
14 - Regression/014 Code_ Logistic regression_en.vtt
12.4 kB
08 - Probability theory/002 Probability vs. proportion_en.vtt
12.4 kB
12 - Correlation/005 Correlation matrix_en.vtt
12.0 kB
17 - Signal detection theory/008 Code_ ROC curves_en.srt
11.9 kB
10 - The t-test family/002 One-sample t-test_en.srt
11.9 kB
14 - Regression/005 Code_ simple regression_en.vtt
11.8 kB
01 - Introductions/003 Statistics guessing game__en.vtt
11.8 kB
06 - Descriptive statistics/002 Accuracy, precision, resolution_en.srt
11.7 kB
08 - Probability theory/014 Sampling variability, noise, and other annoyances_en.vtt
11.6 kB
11 - Confidence intervals on parameters/001 What are confidence intervals and why do we need them__en.vtt
11.6 kB
09 - Hypothesis testing/008 Parametric vs. non-parametric tests_en.vtt
11.6 kB
02 - Math prerequisites/007 The logistic function_en.vtt
11.5 kB
11 - Confidence intervals on parameters/004 Confidence intervals via bootstrapping (resampling)_en.vtt
11.4 kB
06 - Descriptive statistics/017 Statistical _moments__en.vtt
11.4 kB
04 - What are (is_) data_/004 Code_ representing types of data on computers_en.vtt
11.4 kB
12 - Correlation/014 Code_ Spearman correlation and Fisher-Z_en.srt
11.4 kB
07 - Data normalizations and outliers/013 Code_ Euclidean distance for outlier removal_en.vtt
11.3 kB
17 - Signal detection theory/007 Receiver operating characteristics (ROC)_en.srt
11.2 kB
05 - Visualizing data/004 Code_ box plots_en.vtt
11.2 kB
05 - Visualizing data/013 Code_ line plots_en.srt
11.1 kB
09 - Hypothesis testing/009 Multiple comparisons and Bonferroni correction_en.vtt
11.0 kB
05 - Visualizing data/012 Linear vs. logarithmic axis scaling_en.vtt
11.0 kB
07 - Data normalizations and outliers/005 Code_ min-max scaling_en.vtt
11.0 kB
12 - Correlation/012 Nonparametric correlation_ Spearman rank_en.srt
11.0 kB
14 - Regression/010 Polynomial regression models_en.vtt
10.9 kB
18 - A real-world data journey/004 MATLAB_ Import the divorce data_en.vtt
10.9 kB
17 - Signal detection theory/004 Response bias_en.vtt
10.8 kB
13 - Analysis of Variance (ANOVA)/004 The F-test and the ANOVA table_en.srt
10.7 kB
10 - The t-test family/008 Wilcoxon signed-rank (nonparametric t-test)_en.srt
10.7 kB
04 - What are (is_) data_/007 The ethics of making up data_en.srt
10.5 kB
06 - Descriptive statistics/015 QQ plots_en.srt
10.4 kB
17 - Signal detection theory/008 Code_ ROC curves_en.vtt
10.4 kB
10 - The t-test family/002 One-sample t-test_en.vtt
10.3 kB
09 - Hypothesis testing/010 Statistical vs. theoretical vs. clinical significance_en.srt
10.2 kB
08 - Probability theory/019 Tree diagrams for conditional probabilities_en.srt
10.2 kB
12 - Correlation/011 The problem with Pearson_en.srt
10.1 kB
12 - Correlation/013 Fisher-Z transformation for correlations_en.srt
10.1 kB
06 - Descriptive statistics/002 Accuracy, precision, resolution_en.vtt
10.0 kB
12 - Correlation/014 Code_ Spearman correlation and Fisher-Z_en.vtt
9.8 kB
14 - Regression/018 What to do about missing data_en.srt
9.8 kB
17 - Signal detection theory/007 Receiver operating characteristics (ROC)_en.vtt
9.8 kB
02 - Math prerequisites/008 Rank and tied-rank_en.srt
9.8 kB
11 - Confidence intervals on parameters/002 Computing confidence intervals via formula_en.srt
9.7 kB
05 - Visualizing data/013 Code_ line plots_en.vtt
9.6 kB
12 - Correlation/012 Nonparametric correlation_ Spearman rank_en.vtt
9.5 kB
18 - A real-world data journey/005 MATLAB_ More data visualizations_en.srt
9.5 kB
13 - Analysis of Variance (ANOVA)/004 The F-test and the ANOVA table_en.vtt
9.4 kB
10 - The t-test family/008 Wilcoxon signed-rank (nonparametric t-test)_en.vtt
9.3 kB
11 - Confidence intervals on parameters/007 Misconceptions about confidence intervals_en.srt
9.3 kB
09 - Hypothesis testing/005 P-z combinations that you should memorize_en.srt
9.3 kB
16 - Clustering and dimension-reduction/008 K-nearest neighbor classification_en.srt
9.2 kB
04 - What are (is_) data_/007 The ethics of making up data_en.vtt
9.1 kB
06 - Descriptive statistics/015 QQ plots_en.vtt
9.1 kB
10 - The t-test family/010 Mann-Whitney U test (nonparametric t-test)_en.srt
9.1 kB
18 - A real-world data journey/010 Take-home messages_en.srt
8.9 kB
02 - Math prerequisites/003 Scientific notation_en.srt
8.9 kB
17 - Signal detection theory/001 The two perspectives of the world_en.srt
8.9 kB
12 - Correlation/011 The problem with Pearson_en.vtt
8.9 kB
09 - Hypothesis testing/010 Statistical vs. theoretical vs. clinical significance_en.vtt
8.8 kB
12 - Correlation/013 Fisher-Z transformation for correlations_en.vtt
8.8 kB
05 - Visualizing data/011 When to use lines instead of bars_en.srt
8.8 kB
08 - Probability theory/019 Tree diagrams for conditional probabilities_en.vtt
8.8 kB
07 - Data normalizations and outliers/014 Removing outliers by data trimming_en.srt
8.7 kB
05 - Visualizing data/009 Pie charts_en.srt
8.7 kB
04 - What are (is_) data_/002 Where do data come from and what do they mean__en.srt
8.6 kB
14 - Regression/018 What to do about missing data_en.vtt
8.6 kB
02 - Math prerequisites/008 Rank and tied-rank_en.vtt
8.4 kB
11 - Confidence intervals on parameters/002 Computing confidence intervals via formula_en.vtt
8.4 kB
18 - A real-world data journey/005 MATLAB_ More data visualizations_en.vtt
8.4 kB
01 - Introductions/004 Using the Q&A forum_en.srt
8.3 kB
02 - Math prerequisites/006 Natural exponent and logarithm_en.srt
8.2 kB
11 - Confidence intervals on parameters/007 Misconceptions about confidence intervals_en.vtt
8.1 kB
09 - Hypothesis testing/005 P-z combinations that you should memorize_en.vtt
8.1 kB
16 - Clustering and dimension-reduction/008 K-nearest neighbor classification_en.vtt
8.0 kB
05 - Visualizing data/003 Box-and-whisker plots_en.srt
8.0 kB
10 - The t-test family/011 Code_ Mann-Whitney U test_en.srt
7.9 kB
10 - The t-test family/014 _Unsupervised learning__ How many permutations__en.srt
7.9 kB
04 - What are (is_) data_/006 Samples, case reports, and anecdotes_en.srt
7.9 kB
10 - The t-test family/010 Mann-Whitney U test (nonparametric t-test)_en.vtt
7.8 kB
06 - Descriptive statistics/006 The beauty and simplicity of Normal_en.srt
7.8 kB
18 - A real-world data journey/010 Take-home messages_en.vtt
7.8 kB
17 - Signal detection theory/001 The two perspectives of the world_en.vtt
7.7 kB
12 - Correlation/021 Cosine similarity_en.srt
7.7 kB
02 - Math prerequisites/003 Scientific notation_en.vtt
7.7 kB
05 - Visualizing data/011 When to use lines instead of bars_en.vtt
7.6 kB
07 - Data normalizations and outliers/014 Removing outliers by data trimming_en.vtt
7.6 kB
05 - Visualizing data/009 Pie charts_en.vtt
7.5 kB
04 - What are (is_) data_/002 Where do data come from and what do they mean__en.vtt
7.5 kB
07 - Data normalizations and outliers/004 Min-max scaling_en.srt
7.4 kB
01 - Introductions/004 Using the Q&A forum_en.vtt
7.2 kB
06 - Descriptive statistics/013 Interquartile range (IQR)_en.srt
7.2 kB
02 - Math prerequisites/006 Natural exponent and logarithm_en.vtt
7.2 kB
12 - Correlation/020 The subgroups correlation paradox_en.srt
7.1 kB
08 - Probability theory/005 Probability and odds_en.srt
7.1 kB
10 - The t-test family/007 _Unsupervised learning__ Importance of N for t-test_en.srt
7.0 kB
15 - Statistical power and sample sizes/003 Compute power and sample size using G_Power_en.srt
7.0 kB
05 - Visualizing data/003 Box-and-whisker plots_en.vtt
6.9 kB
04 - What are (is_) data_/006 Samples, case reports, and anecdotes_en.vtt
6.9 kB
10 - The t-test family/014 _Unsupervised learning__ How many permutations__en.vtt
6.9 kB
06 - Descriptive statistics/006 The beauty and simplicity of Normal_en.vtt
6.9 kB
10 - The t-test family/011 Code_ Mann-Whitney U test_en.vtt
6.9 kB
12 - Correlation/021 Cosine similarity_en.vtt
6.7 kB
06 - Descriptive statistics/001 Descriptive vs. inferential statistics_en.srt
6.5 kB
17 - Signal detection theory/005 Code_ Response bias_en.srt
6.5 kB
07 - Data normalizations and outliers/016 Non-parametric solutions to outliers_en.srt
6.5 kB
07 - Data normalizations and outliers/004 Min-max scaling_en.vtt
6.4 kB
18 - A real-world data journey/002 Introduction_en.srt
6.4 kB
12 - Correlation/020 The subgroups correlation paradox_en.vtt
6.3 kB
06 - Descriptive statistics/013 Interquartile range (IQR)_en.vtt
6.2 kB
01 - Introductions/001 [Important] Getting the most out of this course_en.srt
6.2 kB
08 - Probability theory/005 Probability and odds_en.vtt
6.2 kB
02 - Math prerequisites/004 Summation notation_en.srt
6.1 kB
10 - The t-test family/007 _Unsupervised learning__ Importance of N for t-test_en.vtt
6.1 kB
01 - Introductions/002 About using MATLAB or Python_en.srt
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07 - Data normalizations and outliers/009 The modified z-score method_en.srt
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17 - Signal detection theory/005 Code_ Response bias_en.vtt
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18 - A real-world data journey/002 Introduction_en.vtt
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03 - IMPORTANT_ Download course materials/001 Download materials for the entire course__en.srt
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01 - Introductions/001 [Important] Getting the most out of this course_en.vtt
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07 - Data normalizations and outliers/009 The modified z-score method_en.vtt
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12 - Correlation/008 _Unsupervised learning__ correlation to covariance matrix_en.vtt
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07 - Data normalizations and outliers/001 Garbage in, garbage out (GIGO)_en.vtt
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03 - IMPORTANT_ Download course materials/001 Download materials for the entire course__en.vtt
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16 - Clustering and dimension-reduction/007 _Unsupervised learning__ dbscan vs. k-means_en.srt
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10 - The t-test family/004 _Unsupervised learning__ The role of variance_en.srt
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16 - Clustering and dimension-reduction/007 _Unsupervised learning__ dbscan vs. k-means_en.vtt
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06 - Descriptive statistics/022 _Unsupervised learning__ asymmetric violin plots_en.srt
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07 - Data normalizations and outliers/011 _Unsupervised learning__ z vs. modified-z_en.srt
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08 - Probability theory/013 Monte Carlo sampling_en.srt
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06 - Descriptive statistics/010 _Unsupervised learning__ central tendencies with outliers_en.vtt
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05 - Visualizing data/005 _Unsupervised learning__ Boxplots of normal and uniform noise_en.srt
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01 - Introductions/25299297-stats-intro-GuessTheTest.zip
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02 - Math prerequisites/001 Should you memorize statistical formulas__en.vtt
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07 - Data normalizations and outliers/018 An outlier lecture on personal accountability_en.vtt
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19 - Bonus section/002 Bonus content.html
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10 - The t-test family/004 _Unsupervised learning__ The role of variance_en.vtt
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12 - Correlation/007 _Unsupervised learning__ average correlation matrices_en.vtt
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07 - Data normalizations and outliers/011 _Unsupervised learning__ z vs. modified-z_en.vtt
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12 - Correlation/016 _Unsupervised learning__ confidence interval on correlation_en.srt
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12 - Correlation/019 _Unsupervised learning__ Does Kendall vs. Pearson matter__en.vtt
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08 - Probability theory/011 _Unsupervised learning__ cdf's for various distributions_en.vtt
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14 - Regression/016 _Unsupervised learning__ Overfit data_en.srt
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01 - Introductions/005 (optional) Entering time-stamped notes in the Udemy video player_en.vtt
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14 - Regression/016 _Unsupervised learning__ Overfit data_en.vtt
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14 - Regression/012 _Unsupervised learning__ Polynomial design matrix_en.vtt
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