Become a Probability & Statistics Master

11h 29m 40s
English
Paid

Master the essential concepts of Probability and Statistics with our comprehensive course featuring 163 lessons, complete with video and text explanations. Test your knowledge with 45 quizzes, complete with solutions, and dive deeper with 8 additional workbooks full of practice problems. "Become a Probability & Statistics Master" is systematically organized into the following sections:

Course Content Overview

  • Visualizing Data

    Learn to create and interpret bar graphs, pie charts, Venn diagrams, histograms, and dot plots for better data visualization.

  • Analyzing Data

    Understand central tendency measures such as mean, median, and mode, along with range, interquartile range (IQR), and box-and-whisker plots.

  • Data Distributions

    Dive into data distributions including mean, variance, and standard deviation, as well as exploring normal distributions and z-scores.

  • Probability Concepts

    Explore probability topics such as union vs. intersection, independent and dependent events, and delve into Bayes' theorem.

  • Discrete Random Variables

    Gain knowledge on binomial, Bernoulli, Poisson, and geometric random variables.

  • Sampling Techniques

    Understand different study types, biases, and the sampling distribution of the sample mean or proportion, including confidence intervals.

  • Hypothesis Testing

    Master inferential statistics, significance levels, type I and II errors, test statistics, and the interpretation of p-values.

  • Regression Analysis

    Learn about scatterplots, correlation coefficients, residuals, the coefficient of determination, RMSE, and chi-square tests for regression.

About the Authors

Krista King

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I’ve always been kind of nerdy… when I was young, my dad would entertain me by writing out math problems on napkins for me to solve. And rather than having this huge, insatiable love for math, the thing I loved was reverse-engineering the information available to solve a problem that seemed tough, but actually wasn’t. In college, I majored in Psychology, but found myself translating the skills I used on those napkin problems to help me in Calculus. For most students, college-level Calculus is a big deal. It’s hard to understand. And tons of students have to get extra help or retake it. And while I personally enjoyed math, I hated hunting around in my textbook for missing information, or spending huge amounts of time solving problems that I knew should have been more straightforward. I looked at what my professors were teaching, took out the confusing vocabulary, noticed patterns in how the problems were actually solved, and eliminated all the confusing theory. And it worked. I passed with flying colors. And when I finished, I worked as a tutor to help other students pass their math classes, too. I was surprised at how well the students I tutored performed on their tests compared to the rest of their class. And even though I graduated with a Psychology degree, I still wanted to tutor. I started making some simple calculus videos for YouTube, and was floored at how much I could help people… and how many people I could help with just one video. Watching my YouTube channel grow to thousands and thousands of subscribers gave me the idea to take my online tutoring to the next level. So I started Krista King Math, where I teach math students easier ways to think about and solve hard math problems, helping them pass their classes with good grades and graduate on time. I also really wanted to start it because I noticed there wasn’t anything out there exactly like Krista King Math. There’s certainly plenty of virtual math tutors for hire, but most of them follow a traditional textbook method. And none of them offer you unlimited hours and subjects of tutoring for only $39 per month.

udemy

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By connecting students all over the world to the best instructors, Udemy is helping individuals reach their goals and pursue their dreams. Udemy is the leading global marketplace for teaching and learning, connecting millions of students to the skills they need to succeed. Udemy helps organizations of all kinds prepare for the ever-evolving future of work. Our curated collection of top-rated business and technical courses gives companies, governments, and nonprofits the power to develop in-house expertise and satisfy employees’ hunger for learning and development.

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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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