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Statistics for Data Analysts and Scientists

person icon Olanrewaju Oyinbooke

4.6

Statistics for Data Analysts and Scientists

Ultimate course to master practical and business applications of essential statistical tests and concepts

updated on icon Updated on May, 2024

language icon Language - English

person icon Olanrewaju Oyinbooke

English [CC]

category icon Data Science and AI ML,Data & Analytics,Data Analysis,Development

Lectures -32

Resources -1

Duration -2.5 hours

4.6

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Course Description

Welcome to "Statistics for Data Analysts and Scientists" - the ultimate course to help you master the practical and business applications of essential statistical tests and concepts!

Are you struggling to make sense of statistical tests like the Chi-Square test of independence, t-tests, correlation, and Analysis of Variance (ANOVA)? Are you looking to understand how these tests can be applied in real-world situations, and how they can be used to drive critical business decisions?

This comprehensive course is designed to equip you with the knowledge and skills to excel as a data analyst or scientist. You will learn how to conduct and interpret key statistical tests such as the one-sample t-test, independent sample t-test, dependent sample t-test, correlation, simple and multiple linear regression, and one-way ANOVA. You will also gain a deep understanding of key statistical concepts like homoscedasticity of variance, multicollinearity, and homogeneity of variance.

With an exciting and engaging teaching style, this course will take you on a journey of discovery that will transform your understanding of statistics. You will learn through a combination of theory, practical examples, and case studies that will help you understand how statistical tests can be applied in real-world situations.

By the end of this course, you will have the confidence and expertise to apply statistical tests and concepts to drive critical business decisions. You will be able to use statistical tools to gain insights into complex data sets, and you will be equipped with the skills to communicate these insights to key stakeholders.

So, what are you waiting for? Sign up for "Statistics for Data Analysts and Scientists" today, and take the first step towards becoming a master of statistical analysis!

Goals

  • Develop a deep understanding of key statistical concepts, such as homoscedasticity of variance, multicollinearity, and homogeneity of variance
  • Gain the skills to apply statistical tests and concepts to real-world situations and communicate insights to key stakeholders
  • Understand how statistical tools can be used to gain insights into complex data sets and how these insights can be used to drive critical business decisions
  • Learn through practical examples, and case studies that will help them understand how statistical tests can be applied in real-world situations
  • Gain the confidence and expertise to excel as a data analyst or scientist, and apply statistical methods to a wide range of data-driven challenges
  • Understand the practical and business applications of essential statistical tests, including the Chi Square test, t-tests, correlation, Regression, etc
  • Learn how to conduct and interpret key statistical tests, including one-sample t-test, independent sample test,  correlation and linear regression, OneWay ANOVA


Prerequisites

  • No programming or prior experience of statistics required
Statistics for Data Analysts and Scientists

Curriculum

Check out the detailed breakdown of what’s inside the course

Introduction
4 Lectures
  • play icon Welcome to the Course 01:08 01:08
  • play icon Intro to Statistics 04:12 04:12
  • play icon Statistical Scale of Measurement 05:58 05:58
  • play icon Common Terms in Statistics 06:02 06:02
Course Resources
3 Lectures
Tutorialspoint
Understanding Inferential Statistics
1 Lectures
Tutorialspoint
Chi Square Test of Independence
3 Lectures
Tutorialspoint
One Sample t-test
3 Lectures
Tutorialspoint
Independent Sample t-test
3 Lectures
Tutorialspoint
Dependent (Paired) Sample t-test
3 Lectures
Tutorialspoint
Correlation Analysis
3 Lectures
Tutorialspoint
Simple Linear Regression
3 Lectures
Tutorialspoint
Multiple Linear Regression
3 Lectures
Tutorialspoint
One Way Analysis of Variance
3 Lectures
Tutorialspoint

Instructor Details

Olanrewaju Oyinbooke

Olanrewaju Oyinbooke


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