Exploratory Data Analysis for the Public Sector with ggplot faq

instructor Instructor: Christopher Brooks and Paula Lantz instructor-icon
duration Duration: duration-icon

This course provides an introduction to Exploratory Data Analysis (EDA) for the public sector, teaching analytical and technical skills using the R programming language and the ggplot2 library of the tidyverse. Students will learn to explore, visualize, and present data, with a focus on equity and the administrative functions of planning and reporting. Upon completion, students will understand the layered grammar of graphics and its implementation in ggplot2, and be able to develop bar, line, and scatter charts, generate trend lines, and understand histograms, kernel density estimations, violin plots, and ridgeplots.

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Course Feature Course Overview Pros & Cons Course Provider Discussion and Reviews
Go to class

Course Feature

costCost:

Free

providerProvider:

Coursera

certificateCertificate:

Paid Certification

languageLanguage:

English

start dateStart Date:

29th May, 2023

Course Overview

❗The content presented here is sourced directly from Coursera platform. For comprehensive course details, including enrollment information, simply click on the 'Go to class' link on our website.

Updated in [March 06th, 2023]

This course, Exploratory Data Analysis for the Public Sector with ggplot, provides an introduction to the core pillars of the public sector and the core functions of public administration through statistical Exploratory Data Analysis (EDA). Students will learn analytical and technical skills using the R programming language to explore, visualize, and present data, with a focus on equity and the administrative functions of planning and reporting. Technical skills in this course will focus on the ggplot2 library of the tidyverse, and include developing bar, line, and scatter charts, generating trend lines, and understanding histograms, kernel density estimations, violin plots, and ridgeplots. These skills are enhanced with lessons on best practices for good information visualization design. Upon completing this course, students will understand the layered grammar of graphics and its implementation in ggplot2, all while exploring a diverse set of authentic public datasets. All coursework is completed in RStudio in Coursera without the need to install additional software.

This course is the second of four courses within the Data Analytics in the Public Sector with R Specialization. It is ideal for current or early-career professionals working in the public sector looking to gain skills in analyzing public data effectively. It is also ideal for current data analytics professionals or students looking to enter the public sector.

[Applications]
Upon completing this course, learners will be able to apply the skills they have learned to their own public sector data. They will be able to use the ggplot2 library to explore, visualize, and present data, with a focus on equity and the administrative functions of planning and reporting. Learners will also be able to develop bar, line, and scatter charts, generate trend lines, and understand histograms, kernel density estimations, violin plots, and ridgeplots. Additionally, learners will be able to apply best practices for good information visualization design.

[Career Paths]
1. Data Analyst: Data Analysts are responsible for collecting, organizing, and analyzing data to help inform decision-making. They use a variety of tools and techniques, such as Exploratory Data Analysis (EDA) with ggplot2, to identify trends and patterns in data. Data Analysts must be able to communicate their findings to stakeholders in a clear and concise manner. As the public sector continues to embrace data-driven decision-making, the demand for Data Analysts is expected to grow.

2. Data Scientist: Data Scientists are responsible for developing and implementing advanced analytics techniques to uncover insights from data. They use a variety of tools and techniques, such as Exploratory Data Analysis (EDA) with ggplot2, to identify trends and patterns in data. Data Scientists must be able to communicate their findings to stakeholders in a clear and concise manner. As the public sector continues to embrace data-driven decision-making, the demand for Data Scientists is expected to grow.

3. Data Visualization Specialist: Data Visualization Specialists are responsible for creating visual representations of data to help stakeholders understand complex information. They use a variety of tools and techniques, such as Exploratory Data Analysis (EDA) with ggplot2, to create charts, graphs, and other visualizations. Data Visualization Specialists must be able to communicate their findings to stakeholders in a clear and concise manner. As the public sector continues to embrace data-driven decision-making, the demand for Data Visualization Specialists is expected to grow.

4. Business Intelligence Analyst: Business Intelligence Analysts are responsible for developing and implementing data-driven solutions to help organizations make better decisions. They use a variety of tools and techniques, such as Exploratory Data Analysis (EDA) with ggplot2, to identify trends and patterns in data. Business Intelligence Analysts must be able to communicate their findings to stakeholders in a clear and concise manner. As the public sector continues to embrace data-driven decision-making, the demand for Business Intelligence Analysts is expected to grow.

[Education Paths]
Recommended Degree Paths:
1. Bachelor of Science in Data Science: This degree program provides students with the skills and knowledge to analyze and interpret data, develop data-driven solutions, and create visualizations to communicate insights. Students will learn the fundamentals of data science, including data mining, machine learning, and predictive analytics. They will also gain experience in programming languages such as Python, R, and SQL. This degree is ideal for those looking to pursue a career in the public sector, as it provides the necessary skills to analyze and interpret public data.

2. Master of Science in Public Administration: This degree program provides students with the skills and knowledge to effectively manage public organizations. Students will learn the fundamentals of public administration, including budgeting, policy analysis, and public management. They will also gain experience in data analysis, research methods, and program evaluation. This degree is ideal for those looking to pursue a career in the public sector, as it provides the necessary skills to analyze and interpret public data.

3. Master of Science in Data Science: This degree program provides students with the skills and knowledge to analyze and interpret data, develop data-driven solutions, and create visualizations to communicate insights. Students will learn the fundamentals of data science, including data mining, machine learning, and predictive analytics. They will also gain experience in programming languages such as Python, R, and SQL. This degree is ideal for those looking to pursue a career in the public sector, as it provides the necessary skills to analyze and interpret public data.

4. Master of Science in Business Analytics: This degree program provides students with the skills and knowledge to analyze and interpret data, develop data-driven solutions, and create visualizations to communicate insights. Students will learn the fundamentals of business analytics, including data mining, machine learning, and predictive analytics. They will also gain experience in programming languages such as Python, R, and SQL. This degree is ideal for those looking to pursue a career in the public sector, as it provides the necessary skills to analyze and interpret public data.

Developing Trends:
1. Data Science: Data science is becoming increasingly important in the public sector, as organizations are looking to leverage data to make better decisions and improve outcomes. As a result, there is a growing demand for data scientists with the skills and knowledge to analyze and interpret public data.

2. Machine Learning: Machine learning is becoming increasingly important in the public sector, as organizations are looking to leverage data to make better decisions and improve outcomes. As a result, there is a growing demand for data scientists with the skills and knowledge to develop machine learning models and interpret public data.

3. Predictive Analytics: Predictive analytics is becoming increasingly important in the public sector, as organizations are looking to leverage data to make better decisions and improve outcomes. As a result, there is a growing demand for data scientists with the skills and knowledge to develop predictive models and interpret public data.

4. Visualization: Visualization is becoming increasingly important in the public sector, as organizations are looking to leverage data to make better decisions and improve outcomes. As a result, there is a growing demand for data scientists with the skills and knowledge to create visualizations to communicate insights and interpret public data.

Pros & Cons

Pros Cons
  • pros

    Introduces R Studio plots

  • pros

    Focuses on Data Analysis

  • pros

    Explores Public Sector

  • cons

    Limited to ggplot

  • cons

    No other software explored

  • cons

    No other topics discussed

Course Provider

Provider Coursera's Stats at AZClass

Discussion and Reviews

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