Inferential Statistics Free Course

Inferential Statistics

star 4.55  Beginner level 1.5 learning hrs 4.8K+ Learners

Instructor:

Mr. Anirudh Rao

Key Highlights

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About this course

Statistics is one of the most important fundamental components that sees its usage in almost all of the domains that use metrics of sorts. Inferential statistics is a popular division in the world of statistics that deals with making inferences about experiments at hand and/or with trackable metrics. The advantage is this, inferential statistics can process numerical data and categorical data with ease. This makes its usage seep into domains and whip up applications that we never thought of before. Since it is a key component of many other domains and a vital part of statistics itself, we here at Great Learning have come up with this course to help you get started with all the fundamentals and to help you build your skillsets in statistics.
 

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Course outline

Introduction to Statistics

Statistics is the discipline of science that deals with studying the collection of data, analyzing, interpreting, and presenting empirical data. It explores the variation in the set of data.

Data Collection for Statistics

Statistics uses many approaches to collect the data for statistical analysis. Direct observation, Experiments, and surveys are the most popular methods to obtain data for statistical analysis. The survey collects data from people through Gallup polls, pre-election polls, marketing surveys, and other forms. 

Types of Statistical Analysis

Descriptive Statistical analysis deals with organizing and interpreting data using graphical and numerical methods, such as Inferential Statistical Analysis, Predictive Analysis, Prescriptive Analysis, Casual Analysis, Mechanistic Analysis are the standard statistical analysis techniques used in Descriptive Statistics.

Deep Dive into Inferential Statistics

Probability and Central Limit Theorem

Understanding Hypothesis Testing

This module starts by explaining what hypothesis testing is. Further, you will learn about two types of hypothesis testing, the process involved in it, and the crucial terms one must know in hypothesis testing in detail.

 

Chi Square Test and ANOVA

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Inferential Statistics

rating icon 4.55

1.5 Hours

Beginner

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4.8K+ learners enrolled so far

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Learner reviews of the Free Courses

4.55
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Reviewer Profile

5.0

Country Flag United Arab Emirates
“Engaging and Well-Structured Course”
I really enjoyed how the curriculum was well-organized and easy to follow. The quizzes and assignments provided a great way to test my understanding. The practical tools and skills covered were highly relevant, and the depth of the topics was just right. Overall, it was a rewarding learning experience that kept me engaged throughout.
Reviewer Profile

5.0

Country Flag Nigeria
“Highlight of Your Learning Experience”
I loved how the course combined videos, quizzes, and hands-on activities to keep things interesting and cater to different learning styles. It was a comprehensive experience that not only increased my knowledge but also built my confidence in applying these skills.
Reviewer Profile

5.0

“My Learning Experience Has Been Transformative, Fostering Critical Thinking and Adaptability”
I enjoyed how the course simplified complex statistical concepts, especially hypothesis testing. The practical examples made the application of inferential statistics clear and relevant to real-world scenarios.
Reviewer Profile

5.0

“I Was Very Happy to Learn This Fun Course”
Such courses increase students’ awareness and knowledge and strengthen them in implementing their future work and projects. I would like to thank you and wish you success.

Our course instructor

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Mr. Anirudh Rao

Machine Learning Expert

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778K+ Learners
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79 Courses
Anirudh has been working in the field of Data Science and has expertise over Python, Machine Learning and other concepts in the field of data analysis. He is also proficient in the concept of Deep Learning and its usage in a production environment. Expertise extends towards working on various projects in the domain of Artificial Intelligence and Neural Networks as well.

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