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Statistics Essentials for Analytics ( S007 )

4.5 + (25,859) Students Ratings

This is a self-paced course from IQ Training’s which helps you to understand various Statistical Techniques from the very basics and also understand how each technique is employed on a real-world data set for analysis and insights. In this course, you will understand, analyze and predict the actual phenomena of Data Science through its Statistics and methods which are considered as the backend of Data Science. Machine learning employs different techniques and theories which are drawn from the fields of  statistic & probabilistic

Course Price :

₹6,209
₹6,899
10%
off

Live Instructor

Available

Self Paced

Think Bigger Advantage

Live Online Classes

All our Classes are Live Instrucotor led online sessions. You can attend at the comfort of your place and Login to our Classes.

LMS (Learning Management System)

LMS will help you to organize your all training material, session videos and review at later date. You can access LMS anytime and review your completed classes. If you miss any class, then you can review the missed class in LMS.

Flexible Schedule

For some reasons, you can not attend the Classes, we can enroll you in the next possible classes. we assure flexibility in class schdules.

Lifetime Access to Learning Platform

You will get Lifetime free access to LMS(Learning Mangement System) You can access all Videos, class room assignments, quizzes, Projects for Life time. You will also get free video sessions for Life time.

Highest Completion Rate

We have the highest course completion rate in the Industry. If you miss a class, you can opt for the missed class in different batch. We assure you the best training possible for you to succeed.

Certificate of Completion

We provide you the Industry recognized Certification of Course completion This certificate will sometimes helps you to get reimbursement of training expenses by your company.

Training Schedule
Batch Start Date Days of Training Weekday/ Weekend Timings
 
 
 
 
 

Course Curriculum

Objectives: At the end of this Data 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 the techniques of Sampling
  • Understand Data representation

 

Topics:

  • Data Types Introduction
  • Numerical parameters to represent data

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

  • Understand probability Rules
  • Understand about dependent and independent events
  • Implementation of  conditional, marginal and joint probabilities by using Bayes Theorem
  • Understand Probability Distribution
  • Explain Central Limit Theorem

 

Topics:

  • Uses of probability
  • Importance of probability
  • Bayesian Inference
  • Concepts of Density
  • Normal Distribution Curve

Objectives: By the end of this Statistical Inference module, you should be able to:

  • Understand point estimation concepts by 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

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

  • Understand association and dependence concepts.
  • Discuss causation and correlation
  • Understand the concept of covariance
  • Discuss Simpson’s paradox
  • Illustrate the Techniques of Clustering

 

Topics:

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

Objectives: At the end of this testing 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 and its types
  • Non- Parametric Test
  • Experimental Designing
  • A/B testing

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 Details

After the completion of this Statistics Essentials for Analytics course, you should be able to:

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

The course is designed for professionals who want to learn all the important statistics required for Data Science and Data analytics. 

The following professionals can opt for this course:

  • Developers aspiring to be a 'Data Scientist'
  • Analytics Managers and Business Analysts who want to understand Machine Learning (ML) Techniques
  • Information Architects who want to gain Predictive Analytics Experience
  • 'R' professionals for captivating and analyzing Big Data
  • Analysts who want to understand the methodologies of Data Science.

Statistics Essentials for Analytics Ceritficate

Statistics Essentials for Analytics Reviews

25,859

Total number of reviews

4.5

Aggregate review score

80%

Course completion rate

Statistics Essentials for Analytics Features

Live Online Classes

All our Classes are Live Instructor led online sessions. You can attend at the comfort of your place and Login to our Classes.

LMS (Learning Management System)

LMS will help you to organize your all training material, session videos and review at later date. You can access LMS anytime and review your completed classes. If you miss any class, then you can review the missed class in LMS.

Flexible Schedule

For some reasons, you can not attend the Classes, we can enroll you in the next possible classes. we assure flexibility in class schedules.

Lifetime Access to Learning Platform

You will get Lifetime free access to LMS(Learning Mangement System) You can access all Videos, class room assignments, quizzes, Projects for Life time. You will also get free video sessions for Life time.

Highest Course Completion Rate

We have the highest course completion rate in the Industry. If you miss a class, you can opt for the missed class in different batch. We assure you the best training possible for you to succeed.

Certificate of completion

We provide you the Industry recognized Certification of Course completion This certificate will sometimes helps you to get reimbursement of training expenses by your company.

Like the course? Enroll Now

Structure your learning and get a certificate to prove it.

Statistics Essentials for Analytics FAQs

You will never miss a class at IQ Online Training! You can choose either of the two options:

  1. View the recorded session of the class available in your LMS or
  2. You can attend the missed session in any other live batch.

After the enrolment, the LMS access will be instantly provided to you able to access for lifetime which includes complete set of previous class recordings/PPTs/PDFs/assignments. You can start learning right away.

Your access to the Support Team is for lifetime. Our team will help you in resolving queries, during and after the course.

Yes, once enrollment has done for course. Access to the course material will be available for lifetime.

You can Call our support numbers listed in site OR Email us at info@iqtrainings.com.

You can view in-depth class sample recordings before the enrollment. Experience the complete learning instead of a demo session with our expertise.

All the instructors are Industry experts with minimum 10-12 yrs of relevant IT experience. They are subject matter experts and are well trained for providing an awesome learning experience to the participants.

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