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Statistics Essentials for Analytics

Statistics Essentials for Analytics

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A self-paced course that helps you to understand the various Statistical Techniques from the very basics and how each technique is employed on a real world data set to analyze and conclude insights. Statistics and its methods are the backend of Data Science to "understand, analyze and predict actual phenomena". Machine learning employs different techniques and theories drawn from statistical & probabilistic fields.

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Online self paced classes

Online Self Learning Courses are designed for self-directed training, allowing participants to begin at their convenience with structured training and review exercises to reinforce learning. You'll learn through videos, PPTs and complete assignments, projects and other activities designed to enhance learning outcomes, all at times that are most convenient to you.

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Curriculum

Understanding the Data

Objectives: At the end of this Module, you should be able to:

Understand various data types
Learn Various variable types
List the uses of variable types
Explain Population and Sample
Discuss sampling techniques
Understand Data representation

Topics:

Introduction to Data Types
Numerical parameters to represent data

b. Mode

c. Median

d. Sensitivity

e. Information Gain

Statistical parameters to represent data

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Probability and its uses

Objectives: At the end of this Module, you should be able to:

Understand rules of probability
Learn about dependent and independent events
Implement conditional, marginal and joint probability using Bayes Theorem
Discuss probability distribution
Explain Central Limit Theorem

Topics:

Uses of probability
Need of probability
Bayesian Inference
Density Concepts
Normal Distribution Curve

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Statistical Inference

Objectives: At the end of this Module, you should be able to:

Understand concept of point estimation using confidence margin
Draw meaningful inferences using margin of error
Explore hypothesis testing and its different levels

Topics:

Point Estimation
Confidence Margin
Hypothesis Testing
Levels of Hypothesis Testing

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Data Clustering

Objectives: At the end of this module, you should be able to:

Understand concept of association and dependence
Explain causation and correlation
Learn the concept of covariance
Discuss Simpson’s paradox
Illustrate Clustering Techniques

Topics:

Association and Dependence
Causation and Correlation
Covariance
Simpson’s Paradox
Clustering Techniques

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Testing the Data

Objectives: At the end of this module, you should be able to:

Understand Parametric and Non-parametric Testing
Learn various types of parametric testing
Discuss experimental designing
Explain a/b testing

Topics:

Parametric Test
Parametric Test Types
Non- Parametric Test
Experimental Designing
A/B testing

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Regression Modelling

Objectives: At the end of this module, you should be able to:

Understand the concept of Linear Regression
Explain Logistic Regression
Implement WOE
Differentiate between heteroscedasticity and homoscedasticity
Learn concept of residual analysis

Topics:

Logistic and Regression Techniques
Problem of Collinearity
WOE and IV
Residual Analysis
Heteroscedasticity
Homoscedasticity

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Course Description

About The Course

The self-paced Statistics Essentials for Analytics Course has been designed in such a manner that it is easy for a future Data Scientist to get a solid foundation on the concepts. The complete mechanism of Data Science is explained in detail in terms of Statistics and Probability. Data and its types are discussed along with different kind of sampling procedures.

Other essential concepts of Statistics (statistical inference, testing, clustering) are emphasized here as well since that’s a very important part of being a Data Scientist. In addition, you will be introduced to primary machine learning algorithms in this Course.

Course Objectives

After the completion of this course, you should be able to:

Analyze different types of data
Master different sampling techniques
Illustrate Descriptive statistics
Apply probabilistic approach to solve real life complex problems
Explain and derive Bayesian inference
Understand Clustering techniques
Understand Regression modelling
Master Hypothesis
Illustrate Testing the data

Who should go for this course?

The course is designed for all those who want to learn essential statistics required for Data Science and Data analytics. The curated statistics course will help you form a strong foundation for the Data Science and predictive modelling (nowadays Machine Learning) field.

The following professionals can go for this course:

Developers aspiring to be a 'Data Scientist'
Analytics Managers who are leading a team of analysts
Business Analysts who want to understand Machine Learning (ML) Techniques
Information Architects who want to gain expertise in Predictive Analytics
'R' professionals who want to captivate and analyze Big Data
Analysts wanting to understand Data Science methodologies

Pre-requisites

No prerequisites are required for this course.

Why learn Statistics Essentials for Analytics?

Statistics and its methods are the backend of Data Science to "understand, analyze and predict actual phenomena". Machine learning employs different techniques and theories drawn from statistical & probabilistic fields. This Statistics Essentials for Analytics Course enables you to gain knowledge of the essential statistics required for analytics and Data Science, understand the mechanism of popular Machine Learning Algorithms like K-Means Clustering, Regression. The course also takes you through the glimpse of hypothesis testing and its methods enabling you perform test on alternative hypothesis.

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Certification

Edureka’s Proficient in Statistics Certificate Holders work at 1000s of companies like

Statistics Essentials for Analytics Certificate

John Doe

Proficient in Statistics

with Grade X

XYZ1234 31st Jul 2024

The Certificate ID can be verified at www.edureka.co/verify to check the authenticity of this certificate

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Testimonial Reviews

Mohit Sharma

I have been subscribing to Edureka's courses for almost a year now, primarily related to Big Data an ... Read More

D

Deepika

The modules were presented well, and the pace was good, not being too fast, or slow. Overall, the ma ... Read More

R

Rama krishna Gunji

The actual training is yet to begin. After completing the course. Because, Even support staff is mor ... Read More

D

DeepikaStudent

The modules were presented well, and the pace was good, not being too fast, or slow. Overall, the ma ... Read More

Karunakar ReddySenior System Analyst at Santander UK

Edureka has very good instructors and technical support team, I have completed the course BIG DATA & ... Read More

Janardhan SingamaneniPrincipal Data Engineer at Staples

I took kafka and datascience classes with EDUREKA and its overall nice. After thorough scanning of a ... Read More

Video Reviews

Vinayak shares his Edureka learning experience and how our Big Data training helped him achieve his dream career path.

Our learner Balasubramaniam shares his Edureka learning experience and how our training helped him stay updated with evolving technologies.

Sriram speaks about his learning experience with Edureka and how our Hadoop training helped him execute his Big Data project efficiently.

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Projects

How will I execute the Practicals?

The practicals are shown in 'R' which is a open-source analytics tool. The step-wise set-up guide for R will be provided to you.

Course Features

Course Duration

You will undergo self-paced learning where you will get an in-depth knowledge of various concepts that will be covered in the course.

Real-life Case Studies

Towards the end of the course, you will be working on a project where you are expected to implement the techniques learnt during the course.

Assignments

Each module will contain practical assignments, which can be completed before going to next module.

Lifetime Access

You will get lifetime access to all the videos,discussion forum and other learning contents inside the Learning Management System.

Certification

edureka certifies you as an expert in Statistics based on the project reviewed by our expert panel.

Forum

We have a community forum for all our customers that further facilitates learning through peer interaction and knowledge sharing.

FAQ's

Will I Get Placement Assistance?

To help you in this endeavor, we have added a resume builder tool in your LMS. Now, you will be able to create a winning resume in just 3 easy steps. You will have unlimited access to use these templates across different roles and designations. All you need to do is, log in to your LMS and click on the "create your resume" option.

Who are the Instructors at edureka?

All the instructors at edureka are practitioners from the Industry with minimum 10-12 yrs of relevant IT experience. They are subject matter experts and are trained by edureka for providing an awesome learning experience.

What if I have more queries?

You can Call us at +91 98702 76457 /1844 230 6362 ( US Tollfree ) OR Email us at sales@edureka.co . We shall be glad to assist you.

What are the other Data Science Courses offered by Edureka apart from this Course?

Other Data Science courses offered by Edureka are:

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