Statistics for Data Analysts and Scientists 2023
Statistics for Data Analysts and Scientists 2023, available at $44.99, has an average rating of 3.8, with 31 lectures, based on 97 reviews, and has 1157 subscribers.
You will learn about 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 This course is ideal for individuals who are Data analysts who want to improve their statistical skills and knowledge or Scientists who need to understand and analyze statistical data in their research or Business professionals who use data to drive decision-making and want to gain a deeper understanding of statistical concepts and tests or Students studying statistics, data science, or a related field who want to develop a strong foundation in statistical methods or Anyone who is interested in learning more about statistics and how it can be applied in practical settings It is particularly useful for Data analysts who want to improve their statistical skills and knowledge or Scientists who need to understand and analyze statistical data in their research or Business professionals who use data to drive decision-making and want to gain a deeper understanding of statistical concepts and tests or Students studying statistics, data science, or a related field who want to develop a strong foundation in statistical methods or Anyone who is interested in learning more about statistics and how it can be applied in practical settings.
Enroll now: Statistics for Data Analysts and Scientists 2023
Summary
Title: Statistics for Data Analysts and Scientists 2023
Price: $44.99
Average Rating: 3.8
Number of Lectures: 31
Number of Published Lectures: 31
Number of Curriculum Items: 31
Number of Published Curriculum Objects: 31
Original Price: $19.99
Quality Status: approved
Status: Live
What You Will Learn
- 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
Who Should Attend
- Data analysts who want to improve their statistical skills and knowledge
- Scientists who need to understand and analyze statistical data in their research
- Business professionals who use data to drive decision-making and want to gain a deeper understanding of statistical concepts and tests
- Students studying statistics, data science, or a related field who want to develop a strong foundation in statistical methods
- Anyone who is interested in learning more about statistics and how it can be applied in practical settings
Target Audiences
- Data analysts who want to improve their statistical skills and knowledge
- Scientists who need to understand and analyze statistical data in their research
- Business professionals who use data to drive decision-making and want to gain a deeper understanding of statistical concepts and tests
- Students studying statistics, data science, or a related field who want to develop a strong foundation in statistical methods
- Anyone who is interested in learning more about statistics and how it can be applied in practical settings
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!
Course Curriculum
Chapter 1: Introduction
Lecture 1: Introduction to Statistics
Lecture 2: Statistical Scale of Measurement
Lecture 3: Common Terms in Statistics
Chapter 2: Course Resources
Lecture 1: Downloading IBM Statistics
Lecture 2: Course Resources
Lecture 3: Acknowledgement
Chapter 3: Understanding Inferential Statistics
Lecture 1: Intro to Inferential Statistics
Chapter 4: Chi Square Test of Independence
Lecture 1: Chi Square Test of Independence Overview
Lecture 2: Running the Test
Lecture 3: Interpret the Results of Chi Square Test of Independence
Chapter 5: One Sample t-test
Lecture 1: One Sample t-test Overview
Lecture 2: Running the Test
Lecture 3: Interpret the Results of One Sample t-test
Chapter 6: Independent Sample t-test
Lecture 1: Independent Sample t-test Overview
Lecture 2: Running the Test
Lecture 3: Interpret the Results of Independent Sample t-test
Chapter 7: Dependent (Paired) Sample t-test
Lecture 1: Dependent or Paired Sample t-test Overview
Lecture 2: Running the Test
Lecture 3: Interpret the Results of Dependent Sample t-test
Chapter 8: Correlation Analysis
Lecture 1: Pearson Correlation Analysis Overview
Lecture 2: Running the Test
Lecture 3: Interpret the Results of Correlation Analysis
Chapter 9: Simple Linear Regression Analysis
Lecture 1: Simple Linear Regression Analysis Overview
Lecture 2: Running the Test
Lecture 3: Interpret the Results of Simple Linear Regression Analysis
Chapter 10: Multiple Linear Regression Analysis
Lecture 1: Multiple Linear Regression Overview
Lecture 2: Running the Test
Lecture 3: Interpret the Results of Multiple Linear Regression Analysis
Chapter 11: One Way Analysis of Variance
Lecture 1: One Way Analysis of Variance Test Overview
Lecture 2: Running the Test
Lecture 3: Interpret the Results of One Way Analysis of Variance Test
Instructors
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Olanrewaju Oyinbooke
ExSenior Cloud Advocate @ Microsoft| Data Scientist
Rating Distribution
- 1 stars: 1 votes
- 2 stars: 5 votes
- 3 stars: 7 votes
- 4 stars: 26 votes
- 5 stars: 58 votes
Frequently Asked Questions
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