Become a Probability & Statistics Master

11h 29m 40s
English
Paid

Course description

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:

Read more about the course

  • 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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#1: Hi! START HERE: Course overview

All Course Lessons (55)

#Lesson TitleDurationAccess
1
Hi! START HERE: Course overview Demo
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

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