Section 1 : Visualizing data
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Lecture 1 | Introduction to visualizing data | 00:00:45 Duration |
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Lecture 2 | One-way data | 00:09:18 Duration |
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Lecture 3 | Bar graphs and pie charts | 00:19:39 Duration |
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Lecture 4 | Line graphsand ogives | 00:13:59 Duration |
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Lecture 5 | Two-way data | 00:12:55 Duration |
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Lecture 6 | Venn diagrams | 00:14:03 Duration |
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Lecture 7 | Relative frequency tables | 00:11:14 Duration |
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Lecture 8 | Joint distributions | 00:10:36 Duration |
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Lecture 9 | Frequency tables and dot plots | 00:03:42 Duration |
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Lecture 10 | Histograms and stem-and-leaf plots | 00:13:02 Duration |
Section 2 : Analyzing data
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Lecture 1 | Introduction to analyzing data | 00:01:03 Duration |
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Lecture 2 | Central tendency mean, median and mode | 00:13:39 Duration |
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Lecture 3 | Spread range and IQR | 00:11:26 Duration |
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Lecture 4 | Changing the data, and outliers | 00:16:08 Duration |
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Lecture 5 | Box-and-whisker plots | 00:06:20 Duration |
Section 3 : Data distributions
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Lecture 1 | Introduction to data distributions | |
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Lecture 2 | Mean, variance, and standard deviation | 00:15:17 Duration |
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Lecture 3 | Frequency histograms and polygons, and density | 00:10:53 Duration |
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Lecture 4 | Symmetric and skewed distributions and outlier | 00:14:05 Duration |
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Lecture 5 | Normal distributions and z-scores | 00:20:58 Duration |
Section 4 : Probability
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Lecture 1 | Introduction to probability | |
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Lecture 2 | Simple probability | 00:17:13 Duration |
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Lecture 3 | The addition rule, and union vs. intersection. | 00:20:31 Duration |
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Lecture 4 | Independent and dependent events and condition | 00:17:41 Duration |
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Lecture 5 | Bayes' theorem | 00:17:08 Duration |
Section 5 : Discrete random variables
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Lecture 1 | Introduction to discrete random variables | |
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Lecture 2 | Discrete probability | 00:13:09 Duration |
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Lecture 3 | Transforming random variables | 00:07:35 Duration |
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Lecture 4 | Combinations of random variables | 00:15:34 Duration |
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Lecture 5 | Permutations and combinations | 00:10:11 Duration |
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Lecture 6 | Binomial random variables | 00:21:17 Duration |
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Lecture 7 | Poisson distributions | |
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Lecture 8 | At least and at most, and mean, variance, and | 00:13:52 Duration |
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Lecture 9 | Bernoulli random variables | 00:10:37 Duration |
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Lecture 10 | Geometric random variables | 00:18:21 Duration |
Section 6 : Sampling
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Lecture 1 | Introduction to sampling | 00:01:19 Duration |
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Lecture 2 | Types of studies | 00:15:56 Duration |
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Lecture 3 | Sampling and bias | 00:15:40 Duration |
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Lecture 4 | Sampling distribution of the sample mean | 00:22:13 Duration |
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Lecture 5 | Sampling distribution of the sample proportion | 00:19:03 Duration |
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Lecture 6 | Confidence interval for a population mean | 00:22:32 Duration |
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Lecture 7 | Confidence interval for a population proportio | 00:17:12 Duration |
Section 7 : Hypothesis testing
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Lecture 1 | Introduction to hypothesis testing | 00:00:54 Duration |
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Lecture 2 | Inferential statistics and hypotheses | 00:15:25 Duration |
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Lecture 3 | icance level and type I and II errors | 00:13:24 Duration |
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Lecture 4 | est statistics for one- and two-tailed tests | 00:19:50 Duration |
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Lecture 5 | The p-value and rejecting the null | 00:12:46 Duration |
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Lecture 6 | Hypothesis testing for the population proport | 00:09:53 Duration |
Section 8 : Regression
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Lecture 1 | Introduction to regression | 00:01:08 Duration |
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Lecture 2 | Scatterplots and regression | 00:15:51 Duration |
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Lecture 3 | Correlation coefficient and the residual | 00:23:10 Duration |
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Lecture 4 | Coefficient of determination and root-mean-sq | 00:17:01 Duration |
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Lecture 5 | Chi-square tests | 00:22:24 Duration |
Section 9 : Final exam and wrap-up
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Lecture 1 | Wrap-up |
