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Enroll now to become an Analytics expert with EDTIA Statistics Essentials for Analytics Certification Training, upgrade your skills, and lead your professional life.
This course is designed to understand the various Statistical Techniques from the basics and how each technique is employed on an actual world data set to analyze and conclude insights.
Statistics Essentials for Analytics training provides complete knowledge to delegates about Statistical Techniques. The representatives will learn how every technique is employed to analyze and conclude insights into a real-world data set.
Statistics are at the core of sophisticated machine learning algorithms in data science, capturing and translating data patterns into actionable evidence. Data scientists use statistics to gather, review, analyze, draw conclusions from data, and apply quantified mathematical models to appropriate variables.
Statistics are at the core of sophisticated machine learning algorithms in data science, capturing and translating data patterns into actionable evidence. Data scientists use statistics to gather, review, analyze, draw conclusions from data, and apply quantified mathematical models to appropriate variables.
Data analysts require good knowledge of spreadsheets, writing queries, and statistical tools to create charts and dashboards. Modern data analysts also need some programming skills and strong analytical and storytelling skills.
Statistics transform raw data into meaningful results. It is the science behind identifying, collecting, organizing, interpreting, and presenting data. Data could be qualitative or quantitative, and Statistics make information-based decision-making easier.
Developers aspiring to be a 'Data Scientist.' Analytics Managers Business Analysts who want to understand Machine Learning (ML) Techniques Information Architects 'R' professionals who want to captivate and analyze Big Data Analysts wanting to understand Data Science methodologies
Understand various data types Learn Various variable types List the uses of variable types Explain Population and Sample Discuss sampling techniques Understand Data representation
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
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
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
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
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
Edtia Support Team is for a lifetime and will be open 24/7 to help with your questions during and after completing the Statistics Essentials for Analytics Certification Training.
The statistical analysis brings numerous benefits to make the best usage of the vast data available, such as assisting in market research, product development, mapping out the company's growth rate, improving the company's efficiency, etc.
To better understand the Statistics Essentials for Analytics Certification Training, one must learn as per the curriculum.
This Statistics Essentials for Analytics Course enables you to understand the fundamental statistics required for analytics and Data Science and understand the mechanism of popular Machine Learning Algorithms like K-Means Clustering, Regression. The course also gives you a glimpse of hypothesis testing and its methods, enabling you to perform tests on alternative hypotheses.
Statistical learning allows you to use the proper methods to collect the data, use the correct analyses, and present the results. Statistics is an essential method behind creating discoveries in science, making decisions based on data, and making forecasts.
Data scientists work as programmers, researchers, business executives, and more. However, all of these areas have in common the basis of statistics, and thus, statistics in data science is as necessary as understanding programming languages.
Every certification training session is followed by a quiz to assess your course learning.
The Mock Tests Are Arranged To Help You Prepare For The Certification Examination.
A lifetime access to LMS is provided where presentations, quizzes, installation guides & class recordings are available.
A 24x7 online support team is available to resolve all your technical queries, through a ticket-based tracking system.
For our learners, we have a community forum that further facilitates learning through peer interaction and knowledge sharing.
Successfully complete your final course project and Edtia will provide you with a completion certification.
Statistics Essentials for Analytics Training demonstrates that the holder has the proficiency and aptitudes to work with Statistics Essentials for Analytics.
By enrolling in Statistics Essentials for Analytics and completing the module, you can get the Edtia Statistics Essentials for Analytics Training Certification.
Industry-designed training in Data Analytics can assist you in fast-track your profession and applying for the top-paying positions. Data Analytics is a vital domain in today's data-driven world, where 90% of the data includes been created in the last two years alone.
Statistics Essentials for Analytics might be proper for you if you're ready for a career in a stable and high-paying field, and this Certification is the place to start.
Discover your perfect program in our courses.
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