Last updated 3/2023Course Language EnglishCourse Caption English [Auto]Course Length 16:20:30 to be exact 58830 seconds!Number of Lectures 103
This course includes:
16.5 hours hours of on-demand video
8 article
Certificate of completion
8 additional resources
Descriptive Statistics
Visualizing Data
Probability Theory
Bayesian Statistics
Discrete Distributions (Binomial, Poisson and More)
Continuous Distributions (Normal and Others)
Hypothesis Tests
Regression
Type I and Type II Errors
Chi-Squared Test
This is course designed to take you from beginner to expert in probability and statistics. It is designed to be practical, hands on and suitable for anyone who wants to use statistics in data science, business analytics or any other field to make better informed decisions.Videos packed with worked examples and explanations so you never get lost, and every technique covered is implemented in Microsoft Excel so that you can put it to use immediately.Key concepts taught in the course are:Descriptive Statistics: Averages, measures of spread, correlation and much more.Cleaning Data: Identifying and removing outliersVisualization of Data: All standard techniques for visualizing data, embedded in Excel.Probability: Independent Events, conditional probability and Bayesian statistics.Discrete Distributions: Binomial, Poisson, expectation and variance and approximations.Continuous Distributions: The Normal distribution, the central limit theorem and continuous random variables.Hypothesis Tests: Using binomial, Poisson and normal distributions, T-tests and confidence intervals.Regression: Linear regression analysis, correlation, testing for correlation, non-linear regression models.Quality of Tests: Type I and Type II errors, power and size, p-hacking.Chi-Squared Tests: The chi-squared distribution and how to use it to test for association and goodness of fit.Much, much more!It requires no prior knowledge, with the exception of 2 optional videos at the end of the continuous distribution chapter, in which knowledge of calculus is required).Who this course is for:Data ScientistsBusiness AnalystsBusiness StudentsPeople studying StatisticsAnyone looking to power their decision making with a thorough understanding of statistics.
Course Content:
Sections are minimized for better readability, click the section title to view the course content
2 Lectures | 04:21
Introduction
01:46
Course Overview
02:35
16 Lectures | 01:48:22
Data for this chapter
00:07
The Mean Average
14:44
The Mean Average - Quiz
4 questions
The Median Average
08:30
The Median Average - Quiz
3 questions
The Modal Average
08:10
The Modal Average - Quiz
2 questions
Comparing Averages
09:12
Comparing Averages - Quiz
2 questions
Quantiles, Range and Inter-Quartile Range
14:02
Quantiles, Range and Inter-Quartile Range - Data
00:02
Quantiles, Range and Inter-Quartile Range - Quiz
3 questions
Standard Deviation and Variance
16:16
Standard Deviation and Variance - Data
00:02
Standard Deviation and Variance - Quiz
3 questions
The Coefficient of Variation
05:23
The Coefficient of Variation - Data
00:02
The Coefficient of Variation - Quiz
4 questions
Skew
12:21
Skew - data
00:02
Skew - Quiz
4 questions
Kurtosis
10:42
Kurtosis - Quiz
2 questions
Correlation Coefficients
08:43
Correlation Coefficients - Data
00:02
Correlation Coefficients - Quiz
4 questions
3 Lectures | 27:40
Anomalies and Outliers
16:54
Anomalies and Outliers - Data
00:02
Anomalies and Outliers - Quiz
4 questions
Coding Your Data
10:44
Coding Your Data - Quiz
3 questions
9 Lectures | 01:19:10
Line Graphs
10:39
Line Graph - Assignment
1 question
Test your ability to create a line graph that effectively shows the changes in a data set over time.
Bar Charts
09:56
Bar Charts - Quiz
3 questions
Dual Axis Charts
06:48
Dual Axis Charts - Assignment
1 question
Have a go at creating a dual axis chart.
Pie Charts
07:14
Pie Charts - Quiz
2 questions
Histograms
12:38
Histograms - Data
00:02
Histograms - Quiz
2 questions
Box Plots
09:11
Box Plots - Quiz
1 question
Cumulative Frequency
10:02
Cumulative Frequency - Quiz
1 question
Comparing Visualizations
12:40
3 Lectures | 26:02
Populations and Samples
06:05
Populations and Samples - Quiz
2 questions
Random Sampling
13:59
Random Sampling - Quiz
3 questions
Non-Random Sampling
05:58
Non-Random Sampling - Quiz
1 question
8 Lectures | 01:15:11
What is Probability?
09:02
What is Probability - Quiz
2 questions
Set Notation
10:11
Set Notation - Quiz
3 questions
Independent Events
03:49
Independent Events - Quiz
3 questions
Mutually Exclusive Events
05:52
Mutually Exclusive Events - Quiz
1 question
Tree Diagrams
06:30
Tree Diagrams - Quiz
2 questions
Venn Diagrams
13:20
Venn Diagram - Quiz
2 questions
Conditional Probability
11:36
Conditional Probability - Quiz
2 questions
Bayes' Theorem
14:51
18 Lectures | 02:30:35
What is a Discrete Random Variable?
07:48
What is a Discrete Random Variable - Quiz
3 questions
Probability Mass Functions
05:47
Probability Mass Functions - Quiz
2 questions
The Expectation of a Discrete Random Variable
07:42
The Expectation of a Discrete Random Variable
1 question
The Variance of a Discrete Random Variable
07:56
The Binomial Distribution - Intro
12:09
The Binomial Distribution Formula - Part 1
17:30
The Binomial Distribution Formula - Part 2
06:50
Using Excel to Solve Binomial Problems
07:58
Applying the Binomial Distribution to Real-World Problems
06:00
Conditional Probability with the Binomial Distribution
06:13
The Poisson Distribution - Intro
06:48
Using Excel to Solve Poisson Problems
08:40
Applying the Poisson Distribution Real-World Problems
07:35
Conditional Probability with the Poisson Distribution
06:26
The Geometric Distribution
08:36
Expectation and Variance of Distributions
07:06
Approximating the Binomial Distribution with the Poisson Distribution
06:25
Derivation of the Poisson Formula
13:06
16 Lectures | 03:12:43
What is a Continuous Distribution?
12:30
The Normal Distribution - Intro
11:11
Calculating Probabilities with the Normal Distribution
14:15
The Inverse Normal Distribution
13:04
Z-Scores
11:17
Finding Unknown Means and Standard Deviations
09:58
Conditional Probability with the Normal Distribution
09:39
Normal Approximations to Binomial Distributions - Part 1
13:11
Normal Approximations to Binomial Distributions - Part 2
08:08
Normal Approximations to Poisson Distributions
14:28
The Central Limit Theorem
22:20
The Limitations of the Central Limit Theorem
09:12
Continuous Random Variables - Probability Density Functions
14:15
Continuous Random Variables - Cumulative Distribution Functions
10:41
Continuous Random Variables - Expectation and Variance
09:08
Continuous Random Variables - Medians and Quartiles
09:26
11 Lectures | 01:59:29
Introduction to Hypothesis Tests - P-Values
11:18
Binomial Hypothesis Tests - Part 1
09:39
Binomial Hypothesis Tests - Part 2
06:36
Binomial Hypothesis Tests - Critical Regions
14:37
Two-Tailed Tests
09:22
Poisson Hypothesis Tests
07:55
Poisson Critical Regions
08:22
Normal Hypothesis Tests
12:24
Normal Hypothesis Tests - Critical Regions
12:41
T-Tests
12:55
Confidence Intervals
13:40
8 Lectures | 01:16:57
Correlation
16:58
Linear Regression
14:59
Evaluating a Regression Line
06:54
Correlation Hypothesis Tests - Intro
07:22
Carrying Out a Test for Correlation
08:16
Correlation Confidence Intervals
05:21
Working with Non-Linear Data - Exponential Models
09:10
Working with Non-Linear Data - Polynomial Models
07:57
4 Lectures | 56:02
Type I Errors
16:29
Type II Errors
10:23
Size and Power
23:29
P-Hacking
05:41
5 Lectures | 01:03:57
The Chi-Squared Distribution
10:57
Chi-Squared Tests for Goodness of Fit
13:43
Grouping
11:51
Using Estimated Parameters in Chi-Squared Tests
12:42
Chi-Squared Tests for Association
14:44
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