Hypothesis Testing - using a single sample
Essential Statistics for Data Science
Data Science and AI ML,Probability & Statistics,Statistics
Lectures -6
Duration -1.5 hours
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Course Description
Hypothesis testing is one of the most essential topics in any statistical study and machine learning algorithms
P-value, alpha and point estimates find their foot prints in most of the statistical and ML studies.
Hence it is important to understand hypothesis testing in as much detail as possible .
The course includes five lectures
Starting the first lecture with the concepts that help you understand Hypothesis testing and what Null & Alternative hypothesis are. How to frame Null & Alternative hypothesis. Explain with a few real time examples
Lecture 2 introduces you to the possible errors namely type I and Type II errors that occurs as a result of the hypothesis testing. Explains how to choose Type I error and balance between Type & II errors
The third lecture is the main lecture and an elaborate one. Helps you understand how to apply the concepts and carry out the hypothesis testing applying all the essential statistical concepts. Explains all the statistical steps and their sequence involved in carrying out the hypothesis test until the conclusion is arrived
The fourth lecture is dedicated for illustration of the hypothesis testing using real time examples
The fifth and the final lecture explains you all about the power of the hypothesis test. The roll of type II error and it probability beta on the power of the test
All the above steps Comprehensively cover all the details in great level of granularity that at the end of the course I am sure you will have a complete and a comprehensive understanding on Hypothesis testing and how to carry them out
Goals
The goal of this course is to make the student understand role of hypothesis testing in statistical studies and machine learning.
To enable the student understand various statistical data dumped in the results of the machine learning algorithms and relate them with their significance
Carryout hypothesis tests involving a single population characteristic by formulating the null & alternative hypotheses, choosing the level of significance foe the test, understand the impacts of the type 1 and type 2 errors, evaluate the power of the test and make statistical decisions at the end
Prerequisites
Students should preferably have some knowledge on random sampling, sample statistic and sample distributions, z statistic, t-statistic and p-value concepts.
Students may choose to go through my courses on the above topics listed below
1. Sampling distributions, point estimate & confidence intervals
2. Random variables and probability distributions
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Curriculum
Check out the detailed breakdown of what’s inside the course
Null & Alternative hypothesis - Explained
1 Lectures
-
Null & Alternative Hypothesis - Explained 14:21 14:21
Type I & II errors
1 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Applying concepts
1 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Illustration with examples
1 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Power of the test and beta
1 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Overview of the course content - Promotion video
1 Lectures
![Tutorialspoint](/market/public/assets/images/loader.gif)
Instructor Details
![Hemakumar Kasala](https://www.tutorialspoint.com/assets/profiles/1220827/profile/200_1498922-1717158419.jpg)
Hemakumar Kasala
Hi I am Hemakumar Kasala.
A passionate instructor who chose to train people in the area of Statistics, Data Science and Machine learning
A post graduate in Electrical Engg., from IIT Kharagpur India,
I have over 30 years of corporate experience working with multinationals like Robert Bosch, Philips and TPVision (subsidiary of TPV)
One of my primary responsibilities during my tenure with Philips/TPVision is to train people across sites worldwide on various technologies that we ventured into.
Currently I am on my own and my activities involve offering training courses on Statistics, Data science and machine learning.
Would love to engage with you and part my knowledge to the best of my understanding on the above subjects.
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