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Testing Statistical Hypotheses in Data science with Python 3

Parametric and nonparametric hypotheses testing using Python 3 advanced statistical libraries with real world data
4.1
4.1/5
(30 reviews)
196 students
Created by Luc Zio

8.7

CourseMarks Score®

8.4

Freshness

8.1

Feedback

8.9

Content

Platform: Udemy
Price: $11.99
Video: 4h 10m
Language: English
Next start: On Demand

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Detailed Analysis

CourseMarks Score®

8.7 / 10

CourseMarks Score® helps students to find the best classes. We aggregate 18 factors, including freshness, student feedback and content diversity.

Freshness Score

8.4 / 10
This course was last updated on 1/2020.

Course content can become outdated quite quickly. After analysing 71,530 courses, we found that the highest rated courses are updated every year. If a course has not been updated for more than 2 years, you should carefully evaluate the course before enrolling.

Student Feedback

8.1 / 10
We analyzed factors such as the rating (4.1/5) and the ratio between the number of reviews and the number of students, which is a great signal of student commitment.

New courses are hard to evaluate because there are no or just a few student ratings, but Student Feedback Score helps you find great courses even with fewer reviews.

Content Score

8.9 / 10
Video Score: 8.2 / 10
The course includes 4h 10m video content. Courses with more videos usually have a higher average rating. We have found that the sweet spot is 16 hours of video, which is long enough to teach a topic comprehensively, but not overwhelming. Courses over 16 hours of video gets the maximum score.
The average video length is 7 hours 24 minutes of 1,300 Python courses on Udemy.
Detail Score: 9.1 / 10

The top online course contains a detailed description of the course, what you will learn and also a detailed description about the instructor.

Extra Content Score: 9.5 / 10

Tests, exercises, articles and other resources help students to better understand and deepen their understanding of the topic.

This course contains:

0 article.
25 resources.
0 exercise.
0 test.

Table of contents

Description

While there are many courses in Python, Machine Learning and other Data science related topics, they tend to be covering several topics in a piece-meal fashion and often superficially.  In other words, those courses are not laser-focused on a given topic that will provide instant mastery.  This course is EXCLUSIVELY about testing parametric and non-parametric 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 hands-on, uses real world 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 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 mark-downs 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 non parametric tests.  This  course is hands-on with real world datasets to help the students understand how to carry on the various tests.

Requirements

• Knowledge of hypotheses testing in statistics and ANOVA concepts
• Basic knowledge of nonparametrics data analysis concepts
• Introductory Python programming language
• Anaconda distribution for Python 3Use of Anaconda Jupyter notebook

You will learn

✓ Be able to confidently compute test statistical hypotheses using Python 3
✓ Be able to interpret your tests results and draw conclusions from the data
✓ Leverage Python as a Data scientist tool to solve hypotheses testing problems

This course is for

• 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

How much does the Testing Statistical Hypotheses in Data science with Python 3 course cost? Is it worth it?

The course costs $11.99. And currently there is a 87% discount on the original price of the course, which was $94.99. So you save $83 if you enroll the course now.
The average price is $19.0 of 1,300 Python courses. So this course is 37% cheaper than the average Python course on Udemy.

Does the Testing Statistical Hypotheses in Data science with Python 3 course have a money back guarantee or refund policy?

YES, Testing Statistical Hypotheses in Data science with Python 3 has a 30-day money back guarantee. The 30-day refund policy is designed to allow students to study without risk.

Are there any SCHOLARSHIPS for this course?

Currently we could not find a scholarship for the Testing Statistical Hypotheses in Data science with Python 3 course, but there is a $83 discount from the original price ($94.99). So the current price is just $11.99.

Who is the instructor? Is Luc Zio a SCAM or a TRUSTED instructor?

Luc Zio has created 7 courses that got 176 reviews which are generally positive. Luc Zio has taught 3050 students and received a 4.3 average review out of 176 reviews. Depending on the information available, Luc Zio is a TRUSTED instructor.

More info about the instructor, Luc Zio

Adjunct faculty of Statistics, Data Scientist
I  have over 20 years of work experience in the field of statistics as an Applied Statistician. For the last  twelve years, I have also  been teaching undergraduate college level statistics courses at St Petersburg College,Florida, USA.As a Data scientist, my interests lie in applying Data science techniques (Exploratory Data Analyses, Statistical analyses and other Machine Learning) to real world data related to many  domains such as Education, Health, Migration, Development, etc.  Through my courses, you will find that most of the datasets that I used are from the UN databases of World countries.

8.7

CourseMarks Score®

8.4

Freshness

8.1

Feedback

8.9

Content

Platform: Udemy
Price: $11.99
Video: 4h 10m
Language: English
Next start: On Demand

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