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Tricia Bagley
In your Exploratory Data Analysis (EDA) in Google Sheets project, you will gain hands-on experience conducting EDA. You will also gain experience interpreting the statistics and visualizations you produce. And while you are conducting EDA, you will gain...
Read more
In your Exploratory Data Analysis (EDA) in Google Sheets project, you will gain hands-on experience conducting EDA. You will also gain experience interpreting the statistics and visualizations you produce. And while you are conducting EDA, you will gain...
Read more
In your Exploratory Data Analysis (EDA) in Google Sheets project, you will gain hands-on experience conducting EDA. You will also gain experience interpreting the statistics and visualizations you produce. And while you are conducting EDA, you will gain insights and apply techniques to aid in choosing a direction for an analysis after EDA is complete. To do this you will work in the free-to-use spreadsheet software Google Sheets.
By the end of this project, you will be able to confidently carry out Exploratory Data Analysis using any spreadsheet software to aid in understanding a data set.
We all want to find the actions in the data we work with, and that we consume personally. We ask ourselves important questions like, “What can my organization do with this?” and “What can I learn from this?” The most critical part of taking in any data is the statistical approach that comes first. Exploratory Data Analysis, or EDA, is an approach to analyzing data sets that summarizes their main characteristics and often uses visualizations like charts and graphs to understand the data before formal modeling or hypothesis testing occurs. Through EDA, we can explore what the data tells us without any manipulation and it gives us the opportunity to uncover high-arching areas of interest so that we don’t miss what the data story tells us.
Note: This course works best for learners who are based in the North America region. We’re currently working on providing the same experience in other regions.
Register for this course and see more details by visiting:
OpenCourser.com/course/0bh1mu/exploratory
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Good to know
Good to know
Know what's good ,
what to watch for , and
possible dealbreakers
Provides an immersive learning experience through project-based work
Imparts crucial data analysis skills in the user-friendly Google Sheets environment
Designed for learners seeking a practical understanding of Exploratory Data Analysis
Helps navigate through data interpretation by exploring patterns and drawing insights
Builds a solid foundation for further data analysis endeavors
Guided by experienced instructor Tricia Bagley, renowned in the field
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Reviews summary
Practical skill building in data analysis
This hands-on Exploratory Data Analysis course is best suited for those based in North America and helps learners engage in the analysis and interpretation of statistical data using free-to-use software, namely Google Sheets. Students who took this course found it to be an excellent building block for learning the process of data analysis and preparing to dive deeper into formal modeling and hypothesis testing.
Hands-on Learning Experience
"gain hands-on experience conducting EDA"
Employs Free-to-Use Google Sheets
"you will work in the free-to-use spreadsheet software Google Sheets"
Best Suited for North America
"works best for learners who are based in the North America region"
Activities
Be better prepared
before
your course. Deepen your understanding
during
and
after
it. Supplement your coursework and achieve mastery of the topics covered
in Exploratory Data Analysis (EDA) in Google Sheets with these
activities:
Refine online spreadsheet skills using Google Sheets
Show steps
Refresh basic spreadsheet skills in Google Sheets to ensure foundational knowledge needed before starting this course.
Browse courses on
Spreadsheet Skills
Show steps
-
Take a Google Sheets tutorial to familiarize yourself with the interface and basic functions.
-
Create a new spreadsheet and input some sample data.
-
Practice using formulas and functions to manipulate and analyze the data.
Read 'Data Science for Business'
Show steps
Gain a broader understanding of data science concepts and their application in business contexts.
View
Data Science for Business: What You Need to...
on Amazon
Show steps
-
Read a few chapters each week.
-
Take notes and highlight important concepts.
Review Google Sheets Basics
Show steps
Review the basics of creating spreadsheets, formatting cells, and working with formulas in Google Sheets.
Browse courses on
Google Sheets
Show steps
-
Read documentation on Google Sheets basics.
-
Create a few practice spreadsheets to put your knowledge into practice.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Attend Google Sheets Tutorials
Show steps
Attend online tutorials to learn additional Google Sheets techniques.
Browse courses on
Google Sheets
Show steps
-
Find a Google Sheets tutorial on a specific topic you want to learn.
-
Follow the steps in the tutorial.
EDA Project
Show steps
Develop a project to perform exploratory data analysis on a dataset using Google Sheets. This project can be completed in several shorter sessions or one longer one.
Browse courses on
Google Sheets
Show steps
-
Choose a dataset that covers a topic of interest to you.
-
Import the dataset into Google Sheets.
-
Explore the data using charts, graphs, and pivot tables.
-
Write a brief report summarizing your findings.
Attend Data Science Meetups
Show steps
Connect with other data science professionals and learn about the latest trends and techniques.
Browse courses on
Data Science
Show steps
-
Find a local data science meetup group.
-
Attend a few meetups.
Volunteer with a Data Science Organization
Show steps
Gain practical experience and make a positive contribution to the community by volunteering with a data science organization.
Browse courses on
Data Science
Show steps
-
Find a data science organization that aligns with your interests.
-
Apply to volunteer.
Refine online spreadsheet skills using Google Sheets
Show steps
Refresh basic spreadsheet skills in Google Sheets to ensure foundational knowledge needed before starting this course.
Browse courses on
Spreadsheet Skills
Show steps
Show steps
Show steps
- Take a Google Sheets tutorial to familiarize yourself with the interface and basic functions.
- Create a new spreadsheet and input some sample data.
- Practice using formulas and functions to manipulate and analyze the data.
Read 'Data Science for Business'
Show steps
Gain a broader understanding of data science concepts and their application in business contexts.
View
Data Science for Business: What You Need to...
on Amazon
Show steps
Show steps
Show steps
- Read a few chapters each week.
- Take notes and highlight important concepts.
Review Google Sheets Basics
Show steps
Review the basics of creating spreadsheets, formatting cells, and working with formulas in Google Sheets.
Browse courses on
Google Sheets
Show steps
Show steps
Show steps
- Read documentation on Google Sheets basics.
- Create a few practice spreadsheets to put your knowledge into practice.
Four other activities
Expand to see all activities and additional details
Show all seven activities
Attend Google Sheets Tutorials
Show steps
Attend online tutorials to learn additional Google Sheets techniques.
Browse courses on
Google Sheets
Show steps
Show steps
Show steps
- Find a Google Sheets tutorial on a specific topic you want to learn.
- Follow the steps in the tutorial.
EDA Project
Show steps
Develop a project to perform exploratory data analysis on a dataset using Google Sheets. This project can be completed in several shorter sessions or one longer one.
Browse courses on
Google Sheets
Show steps
Show steps
Show steps
- Choose a dataset that covers a topic of interest to you.
- Import the dataset into Google Sheets.
- Explore the data using charts, graphs, and pivot tables.
- Write a brief report summarizing your findings.
Attend Data Science Meetups
Show steps
Connect with other data science professionals and learn about the latest trends and techniques.
Browse courses on
Data Science
Show steps
Show steps
Show steps
- Find a local data science meetup group.
- Attend a few meetups.
Volunteer with a Data Science Organization
Show steps
Gain practical experience and make a positive contribution to the community by volunteering with a data science organization.
Browse courses on
Data Science
Show steps
Show steps
Show steps
- Find a data science organization that aligns with your interests.
- Apply to volunteer.
Career center
Learners who complete Exploratory Data Analysis (EDA) in Google Sheets will develop knowledge and skills
that may be useful to these careers:
Biostatistician
Biostatistician
Biostatisticians use their training in statistics and biology to design and analyze studies that investigate the effects of medical treatments and interventions. Exploratory Data Analysis (EDA) is a fundamental part of the biostatistical process, as it allows Biostatisticians to gain insights from data and identify potential problems. This course can help Biostatisticians develop their EDA skills and learn how to use Google Sheets to analyze data. As a result, this course may be useful for those looking to enter or advance in the field of Biostatistics.
Data Visualization Specialist
Data Visualization Specialist
Data Visualization Specialists use their training in design and data analysis to create visualizations that communicate data insights. Exploratory Data Analysis (EDA) is a critical skill for Data Visualization Specialists, as it allows them to understand the data they are working with and identify the most effective ways to visualize it. This course can help Data Visualization Specialists develop their EDA skills and learn how to use Google Sheets to analyze data. As a result, this course may be useful for those looking to enter or advance in the field of Data Visualization.
Statistician
Statistician
Statisticians use their training in statistics and mathematics to collect, analyze, and interpret data. Exploratory Data Analysis (EDA) is a fundamental part of the statistical process, as it allows Statisticians to gain insights from data and identify potential problems. This course can help Statisticians develop their EDA skills and learn how to use Google Sheets to analyze data. As a result, this course may be useful for those looking to enter or advance in the field of Statistics.
Data Scientist
Data Scientist
Data Scientists use their skills in statistics, mathematics, and programming to build models and solve business problems. Exploratory Data Analysis (EDA) is an important part of the data science process, as it helps Data Scientists understand the data they are working with and identify potential problems. This course can help Data Scientists develop their EDA skills and learn how to use Google Sheets to analyze data. As a result, this course may be useful for those looking to enter or advance in the field of Data Science.
Machine Learning Engineer
Machine Learning Engineer
Machine Learning Engineers use their training in computer science and machine learning to build and maintain machine learning models. Exploratory Data Analysis (EDA) is a critical skill for Machine Learning Engineers, as it allows them to understand the data they are working with and identify potential problems. This course can help Machine Learning Engineers develop their EDA skills and learn how to use Google Sheets to analyze data. As a result, this course may be useful for those looking to enter or advance in the field of Machine Learning Engineering.
Data Journalist
Data Journalist
Data Journalists use their training in journalism and data analysis to tell stories with data. Exploratory Data Analysis (EDA) is a critical skill for Data Journalists, as it allows them to quickly and efficiently find insights in data and communicate those insights to the public. This course can help Data Journalists develop their EDA skills and learn how to use Google Sheets to analyze data. As a result, this course may be useful for those looking to enter or advance in the field of Data Journalism.
Data Analyst
Data Analyst
Data Analysts use their training in statistics, mathematics, and data analysis to interpret data and communicate findings to stakeholders. Exploratory Data Analysis (EDA) is a critical skill for Data Analysts, as it allows them to quickly and efficiently gain insights from data. This course can help Data Analysts develop their EDA skills and learn how to use Google Sheets to analyze data. As a result, this course may be useful for those looking to enter or advance in the field of Data Analytics.
Quantitative Analyst
Quantitative Analyst
Quantitative Analysts use their training in mathematics and finance to develop and implement quantitative models. Exploratory Data Analysis (EDA) is a useful skill for Quantitative Analysts, as it allows them to quickly and efficiently identify trends and patterns in financial data. This course can help Quantitative Analysts develop their EDA skills and learn how to use Google Sheets to analyze financial data. As a result, this course may be useful for those looking to enter or advance in the field of Quantitative Analysis.
Epidemiologist
Epidemiologist
Epidemiologists use their training in public health and statistics to investigate and control the spread of diseases. Exploratory Data Analysis (EDA) is a critical skill for Epidemiologists, as it allows them to quickly and efficiently identify patterns and trends in disease data. This course can help Epidemiologists develop their EDA skills and learn how to use Google Sheets to analyze data. As a result, this course may be useful for those looking to enter or advance in the field of Epidemiology.
Market Researcher
Market Researcher
Market Researchers use their training in statistics and marketing to collect, analyze, and interpret data about consumer behavior. Exploratory Data Analysis (EDA) is a critical skill for Market Researchers, as it allows them to gain insights from data and identify potential opportunities. This course can help Market Researchers develop their EDA skills and learn how to use Google Sheets to analyze data. As a result, this course may be useful for those looking to enter or advance in the field of Market Research.
Business Analyst
Business Analyst
Business Analysts use their training in business and data analysis to help organizations improve their performance. Exploratory Data Analysis (EDA) is a valuable skill for Business Analysts, as it allows them to quickly and efficiently identify problems and opportunities. This course can help Business Analysts develop their EDA skills and learn how to use Google Sheets to analyze data. As a result, this course may be useful for those looking to enter or advance in the field of Business Analysis.
Financial Analyst
Financial Analyst
Financial Analysts use their training in finance and mathematics to analyze financial data and make investment recommendations. Exploratory Data Analysis (EDA) is a useful skill for Financial Analysts, as it allows them to quickly and efficiently identify trends and patterns in financial data. This course can help Financial Analysts develop their EDA skills and learn how to use Google Sheets to analyze financial data. As a result, this course may be useful for those looking to enter or advance in the field of Financial Analysis.
Risk Analyst
Risk Analyst
Risk Analysts use their training in finance and risk management to identify and assess risks. Exploratory Data Analysis (EDA) is a valuable skill for Risk Analysts, as it allows them to quickly and efficiently identify potential risks. This course can help Risk Analysts develop their EDA skills and learn how to use Google Sheets to analyze data. As a result, this course may be useful for those looking to enter or advance in the field of Risk Analysis.
UX Researcher
UX Researcher
UX Researchers use their training in psychology and design to research and improve the user experience of products and services. Exploratory Data Analysis (EDA) is a valuable skill for UX Researchers, as it allows them to quickly and efficiently identify user needs and preferences. This course can help UX Researchers develop their EDA skills and learn how to use Google Sheets to analyze data. As a result, this course may be useful for those looking to enter or advance in the field of UX Research.
Data Engineer
Data Engineer
Data Engineers use their training in computer science and data management to build and maintain data systems. Exploratory Data Analysis (EDA) is a useful skill for Data Engineers, as it allows them to understand the data they are working with and identify potential problems. This course can help Data Engineers develop their EDA skills and learn how to use Google Sheets to analyze data. As a result, this course may be useful for those looking to enter or advance in the field of Data Engineering.
For more career information including salaries, visit:
OpenCourser.com/course/0bh1mu/exploratory
Reading list
We've selected nine books
that we think will supplement your
learning. Use these to
develop background knowledge, enrich your coursework, and gain a
deeper understanding of the topics covered in
Exploratory Data Analysis (EDA) in Google Sheets.
Provides a practical guide to data visualization, covering various types of charts and graphs. It teaches how to choose the appropriate visualization for different types of data and how to present data effectively.
Provides a comprehensive overview of statistical methods commonly used in psychology research. It covers topics such as descriptive statistics, inferential statistics, and regression analysis, which provide a foundation for understanding EDA techniques.
Save
Introduces the R programming language and its application in data science. It covers topics such as data manipulation, visualization, and statistical modeling, which are relevant to the course's focus on EDA in Google Sheets.
Teaches data science concepts and techniques from scratch, using Python as the programming language. It covers topics such as data cleaning, feature engineering, and machine learning, which provide a broader perspective on data analysis beyond EDA.
Save
Focuses on practical applications of statistics in data science. It covers topics such as data exploration, hypothesis testing, and regression analysis, which are essential for understanding and interpreting data.
Save
Provides a broader perspective on the field of data science, covering topics such as data ethics, data privacy, and the impact of data on society. It can be helpful for learners who want to understand the context and implications of EDA and data analysis.
Introduces deep learning concepts and techniques using Python. It covers topics such as neural networks, convolutional neural networks, and recurrent neural networks, which can be helpful for learners who want to explore advanced data analysis methods.
Introduces Python for data analysis. It covers topics such as data structures, data manipulation, and data visualization, which are essential for working with data in Python.
Save
Provides a comprehensive overview of data mining techniques. It covers topics such as data preprocessing, clustering, classification, and association analysis, which can be helpful for learners who want to explore advanced data analysis methods beyond EDA.
For more information about how these books relate to this course, visit:
OpenCourser.com/course/0bh1mu/exploratory
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Time
2 hours
Via
Coursera
Institution
Coursera Project Network
Instructor
Tricia Bagley
Good to know
Provides an immersive learning experience through project-based work
Imparts crucial data analysis skills in the user-friendly Google Sheets environment
Designed for learners seeking a practical understanding of Exploratory Data Analysis
Helps navigate through data interpretation by exploring patterns and drawing insights
Builds a solid foundation for further data analysis endeavors
Guided by experienced instructor Tricia Bagley, renowned in the field
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