Become a Probability & Statistics Master

Name: Become a Probability & Statistics Master
Price: 9 USD
Availability: InStock

11h 29m 40s

English

Paid

October 31, 2024

This 163-lesson course includes video and text explanations of everything from Probability and Statistics, and it includes 45 quizzes (with solutions!) and an additional 8 workbooks with extra practice problems, to help you test your understanding along the way. Become a Probability & Statistics Master is organized into the following sections:

Visualizing data, including bar graphs, pie charts, Venn diagrams, histograms, and dot plots
Analyzing data, including mean, median, and mode, plus range and IQR and box-and-whisker plots
Data distributions, including mean, variance, and standard deviation, and normal distributions and z-scores
Probability, including union vs. intersection and independent and dependent events and Bayes' theorem
Discrete random variables, including binomial, Bernoulli, Poisson, and geometric random variables
Sampling, including types of studies, bias, and sampling distribution of the sample mean or sample proportion, and confidence intervals
Hypothesis testing, including inferential statistics, significance levels, type I and II errors, test statistics, and p-values
Regression, including scatterplots, correlation coefficient, the residual, coefficient of determination, RMSE, and chi-square

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#	Title	Duration
1	Hi! START HERE: Course overview	01:28
2	Introduction to visualizing data	00:46
3	One-way data	09:18
4	Bar graphs and pie charts	19:39
5	Line graphs and ogives	13:59
6	Two-way data	12:56
7	Venn diagrams	14:03
8	Relative frequency tables	11:15
9	Joint distributions	10:37
10	Frequency tables and dot plots	03:43
11	Histograms and stem-and-leaf plots	13:02
12	Introduction to analyzing data	01:03
13	Central tendency: mean, median and mode	13:40
14	Spread: range and IQR	11:27
15	Changing the data, and outliers	16:08
16	Box-and-whisker plots	06:20
17	Introduction to data distributions	00:56
18	Mean, variance, and standard deviation	15:17
19	Frequency histograms and polygons, and density curves	10:53
20	Symmetric and skewed distributions and outliers	14:06
21	Normal distributions and z-scores	20:58
22	Introduction to probability	00:47
23	Simple probability	17:13
24	The addition rule, and union vs. intersection	20:31
25	Independent and dependent events and conditional probability	17:41
26	Bayes' theorem	17:08
27	Introduction to discrete random variables	01:01
28	Discrete probability	13:10
29	Transforming random variables	07:35
30	Combinations of random variables	15:34
31	Permutations and combinations	10:12
32	Binomial random variables	21:18
33	Poisson distributions	16:37
34	"At least" and "at most," and mean, variance, and standard deviation	13:53
35	Bernoulli random variables	10:38
36	Geometric random variables	18:22
37	Introduction to sampling	01:19
38	Types of studies	15:57
39	Sampling and bias	15:41
40	Sampling distribution of the sample mean	22:14
41	Sampling distribution of the sample proportion	19:03
42	Confidence interval for a population mean	22:33
43	Confidence interval for a population proportion	17:13
44	Introduction to hypothesis testing	01:02
45	Inferential statistics and hypotheses	15:26
46	Significance level and type I and II errors	13:25
47	Test statistics for one- and two-tailed tests	19:51
48	The p-value and rejecting the null	12:47
49	Hypothesis testing for the population proportion	09:53
50	Introduction to regression	01:08
51	Scatterplots and regression	15:52
52	Correlation coefficient and the residual	23:11
53	Coefficient of determination and root-mean-square error	17:01
54	Chi-square tests	22:25
55	Wrap-up	00:25