Statistics Essentials for Analytics

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Statistics Essentials for Analytics

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.

$159.00 $127.00

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.

Understanding the Data

Answer: 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 a. Mean b. Mode c. Median d. Sensitivity e. Information Gain f. Entropy Statistical parameters to represent data

Probability and its uses

Answer: 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

Statistical Inference

Answer: 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

Data Clustering

Answer: 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

Testing the Data

Answer: 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

Regression Modelling

Answer: 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

About The Course

Answer: 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

Answer: 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?

Answer: 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

Answer: No prerequisites are required for this course.

Why learn Statistics Essentials for Analytics?

Answer: 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.

How will I execute the Practicals?

Answer: 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.

What if I miss a class?

Answer: \"You will never miss a lecture at CertAddda You can choose either of the two options: View the recorded session of the class available in your LMS. You can attend the missed session, in any other live batch.\"

How soon after Signing up would I get access to the Learning Content?

Answer: Post-enrolment, the LMS access will be instantly provided to you and will be available for lifetime. You will be able to access the complete set of previous class recordings, PPTs, PDFs, assignments. Moreover the access to our 24x7 support team will be granted instantly as well. You can start learning right away.

What if I have queries after I complete this course?

Answer: Your access to the Support Team is for lifetime and will be available 24/7. The team will help you in resolving queries, during and after the course.

Do I get any assistance from CertAdda to fill up the application form?

Answer: Yes, we will guide you on how to apply & fill up the ACP® application form in PMI® website. You can use the following link to apply for examination: Apply for Exam

Will I get placement assistance?

Answer: 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.

Is the course material accessible to the students even after the course training is over?

Answer: Yes, the access to the course material will be available for lifetime once you have enrolled into the course.

Who are the instructors?

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

What if I have more queries?

Answer: You can give us a CALL at +91 8178510474 / +91 9967920486 OR email at admin@certadda.com