Overview
 Knowledge of hypotheses testing in statistics and ANOVA concepts
 Basic knowledge of nonparametric data analysis concepts
 Introductory Python programming language
 Anaconda distribution for Python 3
 Use of Anaconda Jupyter notebook
While there are many courses in Python, Machine Learning and other Data sciencerelated topics, they tend to be covering several topics in a piecemeal fashion and often superficially. In other words, those courses are not laserfocused on a given topic that will provide instant mastery. This course is EXCLUSIVELY about testing parametric and nonparametric Statistical Hypotheses in Python 3.
It is highly recommended for Students, Data scientists, Analysts, Programmers and Statisticians who will be using Python as the main tool for data analysis and therefore need to understand HOW Python 3 powerful scientific libraries can be effectively used to tests hypotheses that they were used to performing using R, SAS, SPSS, Matlab or other tools.
The course has several strengths that should not be ignored.
 It is handson, uses realworld data and focuses on testing statistical hypotheses using Python 3.
 It is taught by an Adjunct Professor of Statistics who taught statistics for twelve years
 It is taught by a Data Scientist with a Statistics background and over twenty years of professional experience.
 it is extensive and cover all aspects of testing statistical hypotheses using Python
 It uses Jupyter notebook and markdowns to clearly document the codes and make them professional
 The course uses latex to write the statistical hypotheses to help users understand what is being tested/
In this course, you will learn how to test various statistical hypotheses using Python 3. The course covers the most relevant tests about the population parameters for one, two and many samples. In addition, the course covers ANOVA (Analysis of Variance) and many nonparametric tests. This course is handson with realworld datasets to help the students understand how to carry on the various tests.
 Anyone interested in learning how to test statistical hypotheses using Python
 Data scientists who need to make decisions using sound statistical hypotheses
 Statisticians who want to test statistical hypotheses using Python
 Anyone with the analytical skills who want to use Python as a tool of choice
Course Features
 Lectures 30
 Quizzes 0
 Duration 50 hours
 Skill level All levels
 Language English
 Students 0
 Certificate No
 Assessments Yes
Curriculum

Section 1: Getting started with testing statistical hypotheses with Python 3
This section explains what we need to know about the class and the prerequisites
3
Lecture1.1

Lecture1.2

Lecture1.3


Section 2: Parametric tests of hypotheses using Python
Testing hypotheses in Python based on parametric assumptions
15
Lecture2.1

Lecture2.2

Lecture2.3

Lecture2.4

Lecture2.5

Lecture2.6

Lecture2.7

Lecture2.8

Lecture2.9

Lecture2.10

Lecture2.11

Lecture2.12

Lecture2.13

Lecture2.14

Lecture2.15


Section 3: Hands on Project about testing Hypotheses in Python 3
Project files for the course Testing hypotheses using Python
1
Lecture3.1


SECTION 4: Nonparametric tests of hypotheses using Python
This section is about nonparametric tests of hypotheses using Python.
10
Lecture4.1

Lecture4.2

Lecture4.3

Lecture4.4

Lecture4.5

Lecture4.6

Lecture4.7

Lecture4.8

Lecture4.9

Lecture4.10


Section 5: Conclusion for Testing Statistical Hypotheses in Data science with Python
Concluding remarks for the course
1
Lecture5.1

Instructor
Reviews
Reviews
Average Rating
Detailed Rating