[FreeCourseSite.com] Udemy - Master statistics and machine learning intuition math code

磁力链接/BT种子名称

[FreeCourseSite.com] Udemy - Master statistics and machine learning intuition math code

磁力链接/BT种子简介

种子哈希：f9dc0101ca8d990a05ee3f012e4058f0b5c94fbb
文件大小： 11.72G
已经下载：2128次
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收录时间：2021-04-07
最近下载：2025-06-10

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文件列表

  • 06 Descriptive statistics/039 Code_ data from different distributions.mp4 318.3 MB
  • 16 Clustering and dimension-reduction/193 Code_ dbscan.mp4 302.7 MB
  • 12 Correlation/140 Code_ correlation matrix.mp4 296.5 MB
  • 06 Descriptive statistics/047 Code_ Computing dispersion.mp4 279.5 MB
  • 10 The t-test family/126 Code_ permutation testing.mp4 253.0 MB
  • 16 Clustering and dimension-reduction/189 Code_ k-means clustering.mp4 241.9 MB
  • 12 Correlation/137 Code_ correlation coefficient.mp4 225.1 MB
  • 10 The t-test family/119 Code_ Two-samples t-test.mp4 221.9 MB
  • 12 Correlation/152 Code_ Kendall correlation.mp4 193.4 MB
  • 13 Analysis of Variance (ANOVA)/163 Code_ One-way ANOVA (independent samples).mp4 181.3 MB
  • 14 Regression/175 Code_ Multiple regression.mp4 179.6 MB
  • 08 Probability theory/098 Code_ Law of Large Numbers in action.mp4 174.0 MB
  • 10 The t-test family/122 Code_ Signed-rank test.mp4 170.0 MB
  • 10 The t-test family/116 Code_ One-sample t-test.mp4 165.9 MB
  • 08 Probability theory/092 Code_ sampling variability.mp4 162.7 MB
  • 11 Confidence intervals on parameters/130 Code_ compute confidence intervals by formula.mp4 156.9 MB
  • 13 Analysis of Variance (ANOVA)/156 ANOVA intro, part1.mp4 144.6 MB
  • 07 Data normalizations and outliers/070 Code_ z-score for outlier removal.mp4 143.9 MB
  • 08 Probability theory/081 Code_ compute probabilities.mp4 143.8 MB
  • 11 Confidence intervals on parameters/132 Code_ bootstrapping confidence intervals.mp4 143.4 MB
  • 12 Correlation/138 Code_ Simulate data with specified correlation.mp4 142.8 MB
  • 08 Probability theory/084 Probability mass vs. density.mp4 140.9 MB
  • 05 Visualizing data/028 Code_ histograms.mp4 140.2 MB
  • 09 Hypothesis testing/105 P-values_ definition, tails, and misinterpretations.mp4 138.3 MB
  • 14 Regression/177 Code_ polynomial modeling.mp4 135.6 MB
  • 08 Probability theory/089 Creating sample estimate distributions.mp4 131.3 MB
  • 14 Regression/181 Under- and over-fitting.mp4 127.0 MB
  • 06 Descriptive statistics/054 Code_ Histogram bins.mp4 124.0 MB
  • 08 Probability theory/095 Code_ conditional probabilities.mp4 121.0 MB
  • 13 Analysis of Variance (ANOVA)/166 Code_ Two-way mixed ANOVA.mp4 119.9 MB
  • 06 Descriptive statistics/059 Code_ entropy.mp4 115.7 MB
  • 16 Clustering and dimension-reduction/196 Code_ KNN.mp4 113.9 MB
  • 12 Correlation/144 Code_ partial correlation.mp4 113.5 MB
  • 08 Probability theory/091 Sampling variability, noise, and other annoyances.mp4 111.4 MB
  • 06 Descriptive statistics/056 Code_ violin plots.mp4 110.2 MB
  • 13 Analysis of Variance (ANOVA)/161 The two-way ANOVA.mp4 109.9 MB
  • 12 Correlation/155 Code_ Cosine similarity vs. Pearson correlation.mp4 107.5 MB
  • 16 Clustering and dimension-reduction/192 Clustering via dbscan.mp4 105.6 MB
  • 05 Visualizing data/023 Code_ bar plots.mp4 105.1 MB
  • 12 Correlation/135 Motivation and description of correlation.mp4 101.3 MB
  • 10 The t-test family/118 Two-samples t-test.mp4 98.4 MB
  • 08 Probability theory/100 Code_ the CLT in action.mp4 98.1 MB
  • 09 Hypothesis testing/102 IVs, DVs, models, and other stats lingo.mp4 95.9 MB
  • 06 Descriptive statistics/051 Code_ QQ plots.mp4 94.9 MB
  • 09 Hypothesis testing/109 Parametric vs. non-parametric tests.mp4 91.9 MB
  • 08 Probability theory/094 Conditional probability.mp4 90.1 MB
  • 13 Analysis of Variance (ANOVA)/157 ANOVA intro, part 2.mp4 88.7 MB
  • 05 Visualizing data/025 Code_ box plots.mp4 87.7 MB
  • 06 Descriptive statistics/049 Code_ IQR.mp4 87.7 MB
  • 14 Regression/180 Code_ Logistic regression.mp4 85.3 MB
  • 01 Introductions/003 Statistics guessing game!.mp4 84.2 MB
  • 06 Descriptive statistics/044 Code_ computing central tendency.mp4 80.0 MB
  • 16 Clustering and dimension-reduction/201 Code_ ICA.mp4 77.1 MB
  • 13 Analysis of Variance (ANOVA)/164 Code_ One-way repeated-measures ANOVA.mp4 76.9 MB
  • 16 Clustering and dimension-reduction/198 Code_ PCA.mp4 76.6 MB
  • 17 Signal detection theory/204 Code_ d-prime.mp4 73.1 MB
  • 05 Visualizing data/031 Code_ pie charts.mp4 72.6 MB
  • 14 Regression/173 Multiple regression.mp4 72.4 MB
  • 07 Data normalizations and outliers/063 Code_ z-score.mp4 70.2 MB
  • 08 Probability theory/085 Code_ compute probability mass functions.mp4 69.5 MB
  • 07 Data normalizations and outliers/075 Code_ Data trimming to remove outliers.mp4 68.6 MB
  • 17 Signal detection theory/207 Receiver operating characteristics (ROC).mp4 67.6 MB
  • 10 The t-test family/125 Permutation testing for t-test significance.mp4 66.8 MB
  • 13 Analysis of Variance (ANOVA)/160 The omnibus F-test and post-hoc comparisons.mp4 66.7 MB
  • 14 Regression/167 Introduction to GLM _ regression.mp4 65.3 MB
  • 08 Probability theory/093 Expected value.mp4 62.7 MB
  • 04 What are (is_) data_/017 Types of data_ categorical, numerical, etc.mp4 62.5 MB
  • 12 Correlation/143 Partial correlation.mp4 62.4 MB
  • 10 The t-test family/127 _Unsupervised learning__ How many permutations_.mp4 58.1 MB
  • 17 Signal detection theory/208 Code_ ROC curves.mp4 57.4 MB
  • 16 Clustering and dimension-reduction/188 K-means clustering.mp4 57.2 MB
  • 06 Descriptive statistics/046 Measures of dispersion (variance, standard deviation).mp4 57.1 MB
  • 11 Confidence intervals on parameters/131 Confidence intervals via bootstrapping (resampling).mp4 57.1 MB
  • 10 The t-test family/115 One-sample t-test.mp4 56.7 MB
  • 14 Regression/179 Logistic regression.mp4 55.6 MB
  • 14 Regression/171 Code_ simple regression.mp4 54.9 MB
  • 10 The t-test family/124 Code_ Mann-Whitney U test.mp4 54.6 MB
  • 09 Hypothesis testing/103 What is an hypothesis and how do you specify one_.mp4 51.8 MB
  • 14 Regression/176 Polynomial regression models.mp4 51.6 MB
  • 04 What are (is_) data_/018 Code_ representing types of data on computers.mp4 50.3 MB
  • 14 Regression/174 Standardizing regression coefficients.mp4 49.8 MB
  • 09 Hypothesis testing/108 Type 1 and Type 2 errors.mp4 48.4 MB
  • 13 Analysis of Variance (ANOVA)/158 Sum of squares.mp4 48.3 MB
  • 16 Clustering and dimension-reduction/200 Independent components analysis (ICA).mp4 47.9 MB
  • 13 Analysis of Variance (ANOVA)/162 One-way ANOVA example.mp4 46.7 MB
  • 09 Hypothesis testing/104 Sample distributions under null and alternative hypotheses.mp4 46.1 MB
  • 05 Visualizing data/027 Histograms.mp4 46.0 MB
  • 07 Data normalizations and outliers/073 Code_ Euclidean distance for outlier removal.mp4 46.0 MB
  • 07 Data normalizations and outliers/067 What are outliers and why are they dangerous_.mp4 45.3 MB
  • 16 Clustering and dimension-reduction/197 Principal components analysis (PCA).mp4 44.9 MB
  • 12 Correlation/148 Code_ Spearman correlation and Fisher-Z.mp4 44.9 MB
  • 09 Hypothesis testing/113 Statistical significance vs. classification accuracy.mp4 44.8 MB
  • 08 Probability theory/087 Code_ cdfs and pdfs.mp4 44.3 MB
  • 12 Correlation/136 Covariance and correlation_ formulas.mp4 44.1 MB
  • 14 Regression/168 Least-squares solution to the GLM.mp4 43.6 MB
  • 08 Probability theory/078 What is probability_.mp4 43.3 MB
  • 08 Probability theory/097 The Law of Large Numbers.mp4 42.7 MB
  • 07 Data normalizations and outliers/065 Code_ min-max scaling.mp4 42.5 MB
  • 15 Statistical power and sample sizes/185 What is statistical power and why is it important_.mp4 41.6 MB
  • 17 Signal detection theory/203 d-prime.mp4 41.5 MB
  • 14 Regression/183 Comparing _nested_ models.mp4 41.2 MB
  • 06 Descriptive statistics/042 Measures of central tendency (mean).mp4 40.8 MB
  • 01 Introductions/002 About using MATLAB or Python.mp4 40.8 MB
  • 14 Regression/169 Evaluating regression models_ R2 and F.mp4 40.2 MB
  • 01 Introductions/001 [Important] Getting the most out of this course.mp4 39.9 MB
  • 08 Probability theory/080 Computing probabilities.mp4 39.5 MB
  • 08 Probability theory/079 Probability vs. proportion.mp4 39.5 MB
  • 05 Visualizing data/034 Code_ line plots.mp4 39.2 MB
  • 04 What are (is_) data_/019 Sample vs. population data.mp4 39.1 MB
  • 05 Visualizing data/022 Bar plots.mp4 38.8 MB
  • 14 Regression/170 Simple regression.mp4 38.8 MB
  • 08 Probability theory/086 Cumulative probability distributions.mp4 38.5 MB
  • 07 Data normalizations and outliers/062 Z-score standardization.mp4 38.1 MB
  • 13 Analysis of Variance (ANOVA)/165 Two-way ANOVA example.mp4 37.6 MB
  • 04 What are (is_) data_/016 Where do data come from and what do they mean_.mp4 37.4 MB
  • 06 Descriptive statistics/043 Measures of central tendency (median, mode).mp4 36.1 MB
  • 07 Data normalizations and outliers/068 Removing outliers_ z-score method.mp4 35.3 MB
  • 06 Descriptive statistics/058 Shannon entropy.mp4 34.8 MB
  • 09 Hypothesis testing/107 Degrees of freedom.mp4 34.7 MB
  • 10 The t-test family/114 Purpose and interpretation of the t-test.mp4 33.8 MB
  • 06 Descriptive statistics/038 Data distributions.mp4 33.7 MB
  • 15 Statistical power and sample sizes/187 Compute power and sample size using G_Power.mp4 32.8 MB
  • 12 Correlation/139 Correlation matrix.mp4 32.6 MB
  • 15 Statistical power and sample sizes/186 Estimating statistical power and sample size.mp4 32.6 MB
  • 10 The t-test family/121 Wilcoxon signed-rank (nonparametric t-test).mp4 31.9 MB
  • 12 Correlation/151 Kendall's correlation for ordinal data.mp4 31.8 MB
  • 11 Confidence intervals on parameters/128 What are confidence intervals and why do we need them_.mp4 31.4 MB
  • 09 Hypothesis testing/110 Multiple comparisons and Bonferroni correction.mp4 31.1 MB
  • 10 The t-test family/117 _Unsupervised learning__ The role of variance.mp4 30.1 MB
  • 12 Correlation/147 Fisher-Z transformation for correlations.mp4 30.0 MB
  • 09 Hypothesis testing/112 Cross-validation.mp4 29.8 MB
  • 02 Math prerequisites/006 Should you memorize statistical formulas_.mp4 29.4 MB
  • 08 Probability theory/099 The Central Limit Theorem.mp4 28.1 MB
  • 05 Visualizing data/033 Linear vs. logarithmic axis scaling.mp4 26.9 MB
  • 06 Descriptive statistics/037 Accuracy, precision, resolution.mp4 26.8 MB
  • 07 Data normalizations and outliers/072 Multivariate outlier detection.mp4 26.4 MB
  • 01 Introductions/004 Using the Q&A forum.mp4 25.7 MB
  • 12 Correlation/146 Nonparametric correlation_ Spearman rank.mp4 25.0 MB
  • 06 Descriptive statistics/053 Histograms part 2_ Number of bins.mp4 24.7 MB
  • 07 Data normalizations and outliers/076 Non-parametric solutions to outliers.mp4 24.2 MB
  • 17 Signal detection theory/206 Code_ Response bias.mp4 24.0 MB
  • 17 Signal detection theory/205 Response bias.mp4 23.0 MB
  • 06 Descriptive statistics/052 Statistical _moments_.mp4 22.9 MB
  • 06 Descriptive statistics/036 Descriptive vs. inferential statistics.mp4 22.6 MB
  • 10 The t-test family/123 Mann-Whitney U test (nonparametric t-test).mp4 21.4 MB
  • 10 The t-test family/120 _Unsupervised learning__ Importance of N for t-test.mp4 21.1 MB
  • 13 Analysis of Variance (ANOVA)/159 The F-test and the ANOVA table.mp4 21.0 MB
  • 16 Clustering and dimension-reduction/194 _Unsupervised learning__ dbscan vs. k-means.mp4 21.0 MB
  • 04 What are (is_) data_/021 The ethics of making up data.mp4 20.7 MB
  • 09 Hypothesis testing/111 Statistical vs. theoretical vs. clinical significance.mp4 20.1 MB
  • 11 Confidence intervals on parameters/134 Misconceptions about confidence intervals.mp4 19.6 MB
  • 12 Correlation/141 _Unsupervised learning__ average correlation matrices.mp4 19.4 MB
  • 05 Visualizing data/032 When to use lines instead of bars.mp4 19.0 MB
  • 02 Math prerequisites/012 The logistic function.mp4 18.9 MB
  • 04 What are (is_) data_/020 Samples, case reports, and anecdotes.mp4 18.7 MB
  • 07 Data normalizations and outliers/077 An outlier lecture on personal accountability.mp4 18.7 MB
  • 11 Confidence intervals on parameters/129 Computing confidence intervals via formula.mp4 18.3 MB
  • 06 Descriptive statistics/057 _Unsupervised learning__ asymmetric violin plots.mp4 18.2 MB
  • 09 Hypothesis testing/106 P-z combinations that you should memorize.mp4 18.2 MB
  • 07 Data normalizations and outliers/074 Removing outliers by data trimming.mp4 17.8 MB
  • 06 Descriptive statistics/045 _Unsupervised learning__ central tendencies with outliers.mp4 17.6 MB
  • 12 Correlation/145 The problem with Pearson.mp4 17.5 MB
  • 05 Visualizing data/030 Pie charts.mp4 17.4 MB
  • 08 Probability theory/090 Monte Carlo sampling.mp4 17.1 MB
  • 06 Descriptive statistics/050 QQ plots.mp4 17.1 MB
  • 14 Regression/184 What to do about missing data.mp4 16.9 MB
  • 12 Correlation/149 _Unsupervised learning__ Spearman correlation.mp4 16.7 MB
  • 12 Correlation/153 _Unsupervised learning__ Does Kendall vs. Pearson matter_.mp4 15.7 MB
  • 03 IMPORTANT_ Download course materials/014 Download materials for the entire course!.mp4 15.2 MB
  • 12 Correlation/154 Cosine similarity.mp4 15.0 MB
  • 17 Signal detection theory/202 The two perspectives of the world.mp4 14.7 MB
  • 08 Probability theory/096 Tree diagrams for conditional probabilities.mp4 14.3 MB
  • 02 Math prerequisites/008 Scientific notation.mp4 13.6 MB
  • 02 Math prerequisites/013 Rank and tied-rank.mp4 13.6 MB
  • 16 Clustering and dimension-reduction/195 K-nearest neighbor classification.mp4 13.2 MB
  • 02 Math prerequisites/011 Natural exponent and logarithm.mp4 12.9 MB
  • 08 Probability theory/082 Probability and odds.mp4 12.6 MB
  • 05 Visualizing data/029 _Unsupervised learning__ Histogram proportion.mp4 12.4 MB
  • 07 Data normalizations and outliers/064 Min-max scaling.mp4 12.3 MB
  • 07 Data normalizations and outliers/061 Garbage in, garbage out (GIGO).mp4 12.2 MB
  • 16 Clustering and dimension-reduction/199 _Unsupervised learning__ K-means on PC data.mp4 12.2 MB
  • 17 Signal detection theory/209 _Unsupervised learning__ Make this plot look nicer!.mp4 12.1 MB
  • 16 Clustering and dimension-reduction/190 _Unsupervised learning__ K-means and normalization.mp4 11.8 MB
  • 05 Visualizing data/024 Box-and-whisker plots.mp4 11.7 MB
  • 04 What are (is_) data_/015 Is _data_ singular or plural_!_!!_!.mp4 11.4 MB
  • 06 Descriptive statistics/041 The beauty and simplicity of Normal.mp4 10.8 MB
  • 06 Descriptive statistics/040 _Unsupervised learning__ histograms of distributions.mp4 10.7 MB
  • 12 Correlation/142 _Unsupervised learning__ correlation to covariance matrix.mp4 10.7 MB
  • 06 Descriptive statistics/048 Interquartile range (IQR).mp4 10.4 MB
  • 07 Data normalizations and outliers/069 The modified z-score method.mp4 10.1 MB
  • 08 Probability theory/101 _Unsupervised learning__ Averaging pairs of numbers.mp4 10.0 MB
  • 08 Probability theory/088 _Unsupervised learning__ cdf's for various distributions.mp4 9.8 MB
  • 07 Data normalizations and outliers/071 _Unsupervised learning__ z vs. modified-z.mp4 9.5 MB
  • 12 Correlation/150 _Unsupervised learning__ confidence interval on correlation.mp4 9.3 MB
  • 11 Confidence intervals on parameters/133 _Unsupervised learning__ Confidence intervals for variance.mp4 9.0 MB
  • 01 Introductions/005 (optional) Entering time-stamped notes in the Udemy video player.mp4 8.9 MB
  • 06 Descriptive statistics/060 _Unsupervised learning__ entropy and number of bins.mp4 8.7 MB
  • 05 Visualizing data/026 _Unsupervised learning__ Boxplots of normal and uniform noise.mp4 8.7 MB
  • 16 Clustering and dimension-reduction/191 _Unsupervised learning__ K-means on a Gauss blur.mp4 8.3 MB
  • 02 Math prerequisites/009 Summation notation.mp4 8.2 MB
  • 02 Math prerequisites/007 Arithmetic and exponents.mp4 8.0 MB
  • 02 Math prerequisites/010 Absolute value.mp4 7.3 MB
  • 07 Data normalizations and outliers/066 _Unsupervised learning__ Invert the min-max scaling.mp4 7.2 MB
  • 06 Descriptive statistics/055 Violin plots.mp4 6.8 MB
  • 08 Probability theory/083 _Unsupervised learning__ probabilities of odds-space.mp4 6.2 MB
  • 14 Regression/178 _Unsupervised learning__ Polynomial design matrix.mp4 5.7 MB
  • 14 Regression/182 _Unsupervised learning__ Overfit data.mp4 5.1 MB
  • 14 Regression/172 _Unsupervised learning__ Compute R2 and F.mp4 4.9 MB
  • 05 Visualizing data/035 _Unsupervised learning__ log-scaled plots.mp4 3.9 MB
  • 03 IMPORTANT_ Download course materials/014 statsML.zip 1.5 MB
  • 16 Clustering and dimension-reduction/193 Code_ dbscan.en.srt 52.7 kB
  • 06 Descriptive statistics/039 Code_ data from different distributions.en.srt 49.0 kB
  • 12 Correlation/137 Code_ correlation coefficient.en.srt 43.1 kB
  • 08 Probability theory/092 Code_ sampling variability.en.srt 40.8 kB
  • 06 Descriptive statistics/047 Code_ Computing dispersion.en.srt 39.6 kB
  • 10 The t-test family/126 Code_ permutation testing.en.srt 39.6 kB
  • 16 Clustering and dimension-reduction/189 Code_ k-means clustering.en.srt 36.6 kB
  • 07 Data normalizations and outliers/070 Code_ z-score for outlier removal.en.srt 35.9 kB
  • 10 The t-test family/119 Code_ Two-samples t-test.en.srt 34.3 kB
  • 12 Correlation/140 Code_ correlation matrix.en.srt 34.0 kB
  • 10 The t-test family/116 Code_ One-sample t-test.en.srt 33.4 kB
  • 12 Correlation/155 Code_ Cosine similarity vs. Pearson correlation.en.srt 33.3 kB
  • 06 Descriptive statistics/059 Code_ entropy.en.srt 32.3 kB
  • 14 Regression/167 Introduction to GLM _ regression.en.srt 31.7 kB
  • 08 Probability theory/095 Code_ conditional probabilities.en.srt 31.6 kB
  • 12 Correlation/144 Code_ partial correlation.en.srt 31.4 kB
  • 13 Analysis of Variance (ANOVA)/161 The two-way ANOVA.en.srt 31.3 kB
  • 13 Analysis of Variance (ANOVA)/157 ANOVA intro, part 2.en.srt 30.3 kB
  • 14 Regression/175 Code_ Multiple regression.en.srt 29.8 kB
  • 08 Probability theory/098 Code_ Law of Large Numbers in action.en.srt 29.7 kB
  • 08 Probability theory/089 Creating sample estimate distributions.en.srt 29.6 kB
  • 12 Correlation/135 Motivation and description of correlation.en.srt 29.2 kB
  • 10 The t-test family/122 Code_ Signed-rank test.en.srt 28.7 kB
  • 09 Hypothesis testing/105 P-values_ definition, tails, and misinterpretations.en.srt 28.6 kB
  • 12 Correlation/152 Code_ Kendall correlation.en.srt 28.6 kB
  • 16 Clustering and dimension-reduction/198 Code_ PCA.en.srt 28.3 kB
  • 06 Descriptive statistics/046 Measures of dispersion (variance, standard deviation).en.srt 28.0 kB
  • 13 Analysis of Variance (ANOVA)/156 ANOVA intro, part1.en.srt 27.9 kB
  • 13 Analysis of Variance (ANOVA)/163 Code_ One-way ANOVA (independent samples).en.srt 27.5 kB
  • 11 Confidence intervals on parameters/130 Code_ compute confidence intervals by formula.en.srt 27.4 kB
  • 13 Analysis of Variance (ANOVA)/158 Sum of squares.en.srt 27.2 kB
  • 14 Regression/179 Logistic regression.en.srt 27.2 kB
  • 05 Visualizing data/023 Code_ bar plots.en.srt 27.1 kB
  • 14 Regression/181 Under- and over-fitting.en.srt 27.1 kB
  • 09 Hypothesis testing/102 IVs, DVs, models, and other stats lingo.en.srt 25.9 kB
  • 05 Visualizing data/028 Code_ histograms.en.srt 25.9 kB
  • 14 Regression/169 Evaluating regression models_ R2 and F.en.srt 25.4 kB
  • 08 Probability theory/100 Code_ the CLT in action.en.srt 25.1 kB
  • 06 Descriptive statistics/051 Code_ QQ plots.en.srt 25.1 kB
  • 06 Descriptive statistics/049 Code_ IQR.en.srt 25.0 kB
  • 09 Hypothesis testing/103 What is an hypothesis and how do you specify one_.en.srt 24.9 kB
  • 16 Clustering and dimension-reduction/197 Principal components analysis (PCA).en.srt 24.7 kB
  • 14 Regression/177 Code_ polynomial modeling.en.srt 23.9 kB
  • 09 Hypothesis testing/108 Type 1 and Type 2 errors.en.srt 23.7 kB
  • 08 Probability theory/081 Code_ compute probabilities.en.srt 23.5 kB
  • 17 Signal detection theory/204 Code_ d-prime.en.srt 23.3 kB
  • 11 Confidence intervals on parameters/132 Code_ bootstrapping confidence intervals.en.srt 23.2 kB
  • 16 Clustering and dimension-reduction/192 Clustering via dbscan.en.srt 23.1 kB
  • 07 Data normalizations and outliers/067 What are outliers and why are they dangerous_.en.srt 23.0 kB
  • 13 Analysis of Variance (ANOVA)/166 Code_ Two-way mixed ANOVA.en.srt 22.9 kB
  • 16 Clustering and dimension-reduction/188 K-means clustering.en.srt 22.4 kB
  • 04 What are (is_) data_/017 Types of data_ categorical, numerical, etc.en.srt 22.3 kB
  • 12 Correlation/136 Covariance and correlation_ formulas.en.srt 22.2 kB
  • 13 Analysis of Variance (ANOVA)/162 One-way ANOVA example.en.srt 22.0 kB
  • 06 Descriptive statistics/044 Code_ computing central tendency.en.srt 21.5 kB
  • 12 Correlation/138 Code_ Simulate data with specified correlation.en.srt 21.3 kB
  • 14 Regression/170 Simple regression.en.srt 21.0 kB
  • 05 Visualizing data/031 Code_ pie charts.en.srt 20.7 kB
  • 07 Data normalizations and outliers/063 Code_ z-score.en.srt 20.5 kB
  • 17 Signal detection theory/203 d-prime.en.srt 20.5 kB
  • 14 Regression/173 Multiple regression.en.srt 20.4 kB
  • 06 Descriptive statistics/042 Measures of central tendency (mean).en.srt 20.2 kB
  • 10 The t-test family/118 Two-samples t-test.en.srt 20.2 kB
  • 10 The t-test family/114 Purpose and interpretation of the t-test.en.srt 20.1 kB
  • 13 Analysis of Variance (ANOVA)/160 The omnibus F-test and post-hoc comparisons.en.srt 20.1 kB
  • 08 Probability theory/094 Conditional probability.en.srt 20.1 kB
  • 09 Hypothesis testing/107 Degrees of freedom.en.srt 19.8 kB
  • 16 Clustering and dimension-reduction/201 Code_ ICA.en.srt 19.7 kB
  • 08 Probability theory/084 Probability mass vs. density.en.srt 19.6 kB
  • 13 Analysis of Variance (ANOVA)/164 Code_ One-way repeated-measures ANOVA.en.srt 19.6 kB
  • 14 Regression/174 Standardizing regression coefficients.en.srt 19.6 kB
  • 14 Regression/183 Comparing _nested_ models.en.srt 19.5 kB
  • 16 Clustering and dimension-reduction/196 Code_ KNN.en.srt 19.5 kB
  • 06 Descriptive statistics/043 Measures of central tendency (median, mode).en.srt 19.4 kB
  • 08 Probability theory/078 What is probability_.en.srt 19.1 kB
  • 06 Descriptive statistics/054 Code_ Histogram bins.en.srt 19.0 kB
  • 16 Clustering and dimension-reduction/200 Independent components analysis (ICA).en.srt 18.3 kB
  • 04 What are (is_) data_/019 Sample vs. population data.en.srt 18.3 kB
  • 05 Visualizing data/022 Bar plots.en.srt 18.2 kB
  • 09 Hypothesis testing/113 Statistical significance vs. classification accuracy.en.srt 18.1 kB
  • 06 Descriptive statistics/038 Data distributions.en.srt 17.9 kB
  • 13 Analysis of Variance (ANOVA)/165 Two-way ANOVA example.en.srt 17.8 kB
  • 15 Statistical power and sample sizes/186 Estimating statistical power and sample size.en.srt 17.7 kB
  • 09 Hypothesis testing/112 Cross-validation.en.srt 17.5 kB
  • 10 The t-test family/125 Permutation testing for t-test significance.en.srt 17.4 kB
  • 07 Data normalizations and outliers/075 Code_ Data trimming to remove outliers.en.srt 17.4 kB
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  • 08 Probability theory/099 The Central Limit Theorem.en.srt 16.6 kB
  • 06 Descriptive statistics/058 Shannon entropy.en.srt 16.5 kB
  • 06 Descriptive statistics/056 Code_ violin plots.en.srt 16.5 kB
  • 12 Correlation/143 Partial correlation.en.srt 16.4 kB
  • 08 Probability theory/093 Expected value.en.srt 16.4 kB
  • 12 Correlation/151 Kendall's correlation for ordinal data.en.srt 16.2 kB
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  • 09 Hypothesis testing/104 Sample distributions under null and alternative hypotheses.en.srt 15.6 kB
  • 08 Probability theory/097 The Law of Large Numbers.en.srt 15.3 kB
  • 07 Data normalizations and outliers/072 Multivariate outlier detection.en.srt 15.3 kB
  • 14 Regression/168 Least-squares solution to the GLM.en.srt 15.3 kB
  • 06 Descriptive statistics/053 Histograms part 2_ Number of bins.en.srt 15.3 kB
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  • 15 Statistical power and sample sizes/185 What is statistical power and why is it important_.en.srt 15.2 kB
  • 14 Regression/180 Code_ Logistic regression.en.srt 15.1 kB
  • 08 Probability theory/079 Probability vs. proportion.en.srt 15.1 kB
  • 07 Data normalizations and outliers/068 Removing outliers_ z-score method.en.srt 15.1 kB
  • 08 Probability theory/087 Code_ cdfs and pdfs.en.srt 15.1 kB
  • 12 Correlation/139 Correlation matrix.en.srt 14.5 kB
  • 14 Regression/171 Code_ simple regression.en.srt 14.3 kB
  • 14 Regression/176 Polynomial regression models.en.srt 14.3 kB
  • 01 Introductions/003 Statistics guessing game!.en.srt 14.2 kB
  • 02 Math prerequisites/012 The logistic function.en.srt 14.0 kB
  • 04 What are (is_) data_/018 Code_ representing types of data on computers.en.srt 14.0 kB
  • 11 Confidence intervals on parameters/128 What are confidence intervals and why do we need them_.en.srt 14.0 kB
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  • 06 Descriptive statistics/037 Accuracy, precision, resolution.en.srt 12.2 kB
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  • 14 Regression/184 What to do about missing data.en.srt 10.2 kB
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  • 11 Confidence intervals on parameters/134 Misconceptions about confidence intervals.en.srt 9.7 kB
  • 09 Hypothesis testing/106 P-z combinations that you should memorize.en.srt 9.6 kB
  • 16 Clustering and dimension-reduction/195 K-nearest neighbor classification.en.srt 9.6 kB
  • 10 The t-test family/123 Mann-Whitney U test (nonparametric t-test).en.srt 9.4 kB
  • 02 Math prerequisites/008 Scientific notation.en.srt 9.3 kB
  • 17 Signal detection theory/202 The two perspectives of the world.en.srt 9.3 kB
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  • 07 Data normalizations and outliers/074 Removing outliers by data trimming.en.srt 9.1 kB
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  • 04 What are (is_) data_/016 Where do data come from and what do they mean_.en.srt 8.9 kB
  • 01 Introductions/004 Using the Q&A forum.en.srt 8.7 kB
  • 02 Math prerequisites/011 Natural exponent and logarithm.en.srt 8.6 kB
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  • 10 The t-test family/127 _Unsupervised learning__ How many permutations_.en.srt 8.2 kB
  • 04 What are (is_) data_/020 Samples, case reports, and anecdotes.en.srt 8.2 kB
  • 06 Descriptive statistics/041 The beauty and simplicity of Normal.en.srt 8.1 kB
  • 12 Correlation/154 Cosine similarity.en.srt 8.0 kB
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  • 06 Descriptive statistics/048 Interquartile range (IQR).en.srt 7.5 kB
  • 08 Probability theory/082 Probability and odds.en.srt 7.4 kB
  • 15 Statistical power and sample sizes/187 Compute power and sample size using G_Power.en.srt 7.3 kB
  • 10 The t-test family/120 _Unsupervised learning__ Importance of N for t-test.en.srt 7.3 kB
  • 06 Descriptive statistics/036 Descriptive vs. inferential statistics.en.srt 6.8 kB
  • 17 Signal detection theory/206 Code_ Response bias.en.srt 6.8 kB
  • 07 Data normalizations and outliers/076 Non-parametric solutions to outliers.en.srt 6.7 kB
  • 01 Introductions/001 [Important] Getting the most out of this course.en.srt 6.5 kB
  • 02 Math prerequisites/009 Summation notation.en.srt 6.4 kB
  • 01 Introductions/002 About using MATLAB or Python.en.srt 6.3 kB
  • 07 Data normalizations and outliers/069 The modified z-score method.en.srt 6.3 kB
  • 12 Correlation/142 _Unsupervised learning__ correlation to covariance matrix.en.srt 6.2 kB
  • 07 Data normalizations and outliers/061 Garbage in, garbage out (GIGO).en.srt 6.0 kB
  • 02 Math prerequisites/007 Arithmetic and exponents.en.srt 6.0 kB
  • 03 IMPORTANT_ Download course materials/014 Download materials for the entire course!.en.srt 5.8 kB
  • 06 Descriptive statistics/055 Violin plots.en.srt 5.3 kB
  • 16 Clustering and dimension-reduction/194 _Unsupervised learning__ dbscan vs. k-means.en.srt 4.7 kB
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  • 02 Math prerequisites/010 Absolute value.en.srt 4.4 kB
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  • 07 Data normalizations and outliers/077 An outlier lecture on personal accountability.en.srt 4.4 kB
  • 10 The t-test family/117 _Unsupervised learning__ The role of variance.en.srt 4.4 kB
  • 12 Correlation/141 _Unsupervised learning__ average correlation matrices.en.srt 4.3 kB
  • 18 Bonus section/211 Bonus content.html 4.3 kB
  • 06 Descriptive statistics/057 _Unsupervised learning__ asymmetric violin plots.en.srt 4.1 kB
  • 07 Data normalizations and outliers/071 _Unsupervised learning__ z vs. modified-z.en.srt 4.1 kB
  • 08 Probability theory/090 Monte Carlo sampling.en.srt 4.1 kB
  • 05 Visualizing data/026 _Unsupervised learning__ Boxplots of normal and uniform noise.en.srt 4.0 kB
  • 07 Data normalizations and outliers/066 _Unsupervised learning__ Invert the min-max scaling.en.srt 3.9 kB
  • 01 Introductions/003 stats-intro-GuessTheTest.zip 3.8 kB
  • 05 Visualizing data/029 _Unsupervised learning__ Histogram proportion.en.srt 3.6 kB
  • 12 Correlation/153 _Unsupervised learning__ Does Kendall vs. Pearson matter_.en.srt 3.6 kB
  • 12 Correlation/150 _Unsupervised learning__ confidence interval on correlation.en.srt 3.5 kB
  • 08 Probability theory/088 _Unsupervised learning__ cdf's for various distributions.en.srt 3.5 kB
  • 08 Probability theory/101 _Unsupervised learning__ Averaging pairs of numbers.en.srt 3.4 kB
  • 08 Probability theory/083 _Unsupervised learning__ probabilities of odds-space.en.srt 3.3 kB
  • 01 Introductions/005 (optional) Entering time-stamped notes in the Udemy video player.en.srt 3.3 kB
  • 06 Descriptive statistics/040 _Unsupervised learning__ histograms of distributions.en.srt 3.3 kB
  • 14 Regression/182 _Unsupervised learning__ Overfit data.en.srt 2.9 kB
  • 05 Visualizing data/035 _Unsupervised learning__ log-scaled plots.en.srt 2.6 kB
  • 16 Clustering and dimension-reduction/190 _Unsupervised learning__ K-means and normalization.en.srt 2.6 kB
  • 17 Signal detection theory/209 _Unsupervised learning__ Make this plot look nicer!.en.srt 2.5 kB
  • 04 What are (is_) data_/015 Is _data_ singular or plural_!_!!_!.en.srt 2.5 kB
  • 16 Clustering and dimension-reduction/199 _Unsupervised learning__ K-means on PC data.en.srt 2.4 kB
  • 06 Descriptive statistics/060 _Unsupervised learning__ entropy and number of bins.en.srt 2.1 kB
  • 16 Clustering and dimension-reduction/191 _Unsupervised learning__ K-means on a Gauss blur.en.srt 2.1 kB
  • 11 Confidence intervals on parameters/133 _Unsupervised learning__ Confidence intervals for variance.en.srt 2.0 kB
  • 12 Correlation/149 _Unsupervised learning__ Spearman correlation.en.srt 2.0 kB
  • 18 Bonus section/210 About deep learning.html 1.8 kB
  • 14 Regression/172 _Unsupervised learning__ Compute R2 and F.en.srt 1.5 kB
  • 14 Regression/178 _Unsupervised learning__ Polynomial design matrix.en.srt 1.2 kB
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