Managing, Describing, and Analyzing Data (Coursera)

Managing, Describing, and Analyzing Data (Coursera)

In this course, you will learn the basics of understanding the data you have and why correctly classifying data is the first step to making correct decisions. You will describe data both graphically and numerically using descriptive statistics and R software. You will learn four probability distributions commonly used in the analysis of data. You will analyze data sets using the appropriate probability distribution. Finally, you will learn the basics of sampling error, sampling distributions, and errors in decision-making.

Class Deals by MOOC List - Click here and see Coursera's Active Discounts, Deals, and Promo Codes.

What You Will Learn

  • Calculate descriptive statistics and create graphical representations using R software
  • Solve problems and make decisions using probability distributions
  • Explore the basics of sampling and sampling distributions with respect to statistical inference
  • Classify types of data with scales of measurement

Syllabus

WEEK 1
Data and Measurement
Upon completion of this module, students will be able to use R and R Studio to work with data and classify types of data using measurement scales.

WEEK 2
Describing Data Graphically
Upon completion of this module, students will be able to use R and R Studio to create visual representations of data.

WEEK 3
Describing Data Numerically
Upon completion of this module, students will be able to use R and R Studio to calculate descriptive statistics to describe location, spread and shape of data.

WEEK 4
Probability and Probability Distributions
Upon completion of this module, students will be able to apply the rules and conditions of probability and probability distributions to make decisions and solve problems using R and R Studio.

WEEK 5
Sampling Distributions and Error
Upon completion of this module, students will be able to use R and R Studio to characterize sampling and sampling distributions with respect to statistical inference.

Go to Class
MOOC List is learner-supported. When you buy through links on our site, we may earn an affiliate commission.

Related Courses

Probabilistic Graphical Models 1: Representation (Coursera) Coursera
Stanford University

Probabilistic Graphical Models 1: Representation (Coursera)

Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other. These representations sit at the intersection of statistics and computer science, relying on concepts from probability theory, graph algorithms, machine learning, and more. They are the basis for the state-of-the-art methods in a wide variety of applications, such as medical diagnosis, image understanding, speech recognition, natural language processing, and many, many more. They are also a foundational tool in formulating many machine learning problems.

Nov 23rd 2026
5-12 Weeks
¿Cómo tomar decisiones financieras que agreguen valor? (Coursera) Coursera
Universidad de los Andes

¿Cómo tomar decisiones financieras que agreguen valor? (Coursera)

Los estudiantes al terminar este curso estarán en capacidad de seguir un proceso sistemático y ordenado para la toma de decisiones financieras. Este curso permitirá no solo exponer a los participantes a todos los detalles del proceso de decisión típicos del gerente de finanzas, sino aplicar sus conocimientos a un caso concreto. El proceso comienza con un análisis histórico de la información financiera que luego de usa para la construcción de una tabla de supuestos donde se resumen todas las estimaciones.

Nov 23rd 2026
5-12 Weeks
Civil Registration & Vital Statistics in Population Health (Coursera) Coursera
Johns Hopkins University

Civil Registration & Vital Statistics in Population Health (Coursera)

In this course, you will learn about the role and importance of civil registration and vital statistics (CRVS) systems that are used to track birth, death, and life events. Experts from around the world will explain what CRVS systems are, how they are used, the legal bases for registering vital events, and challenges experienced with CRVS systems.

Nov 23rd 2026
2 Weeks
Estadística y probabilidad (Coursera) Coursera
Universidad Nacional Autónoma de México

Estadística y probabilidad (Coursera)

En este curso podrás apoyar tu formación en temas de estadística y probabilidad I. Más allá de que encuentres aquí un apoyo para lograr una calificación, el curso busca ayudarte a que adquieras los aprendizajes que comprenden temas de estadística descriptiva, datos bivariados y probabilidad, los cuales te serán de utilidad en tu paso por la licenciatura y en tu vida profesional.

Nov 23rd 2026
4 Weeks
Women's Leadership: Boost your skills and drive change (Coursera) Coursera
Inter-American Development Bank - IDB

Women's Leadership: Boost your skills and drive change (Coursera)

In this course, you will be able to learn about the importance of female leadership in Latin America and the Caribbean for the growth and development of economies, democracies, and societies. It focuses on gender equality as a fundamental pillar for sustainable and inclusive growth in the region.

Nov 23rd 2026
5-12 Weeks
Introduction to Technology-Assisted Decision-Making (Coursera) Coursera
University of Leeds

Introduction to Technology-Assisted Decision-Making (Coursera)

Technology-assisted decision-making is increasingly important to modern businesses in a wide variety of fields, including finance, healthcare, marketing, and logistics, among others. It introduces speed and efficiency because substantial amounts of data can be processed efficiently to enable faster, objective, contextual decisions. This online course will introduce you to the fundamental concepts of technology-assisted decision-making and its diverse applications in resource allocation, production planning, transportation, scheduling, and network optimisation.

Nov 23rd 2026
2 Weeks
Statistics and Data Analysis with Excel, Part 1 (Coursera) Coursera
University of Colorado Boulder

Statistics and Data Analysis with Excel, Part 1 (Coursera)

Designed for students with no prior statistics knowledge, this course will provide a foundation for further study in data science, data analytics, or machine learning. Topics include descriptive statistics, probability, and discrete and continuous probability distributions. Assignments are conducted in Microsoft Excel (Windows or Mac versions). Designed to be taken with the follow-up course, “Statistics and Data Analysis with Excel, Part 2.”

Nov 23rd 2026
5-12 Weeks
Design Thinking for Data Professionals (Coursera) Coursera
Fractal Analytics

Design Thinking for Data Professionals (Coursera)

This course provides a comprehensive understanding of Human-Centered Design (HCD) principles and practices. Participants will analyze cognitive and emotional factors influencing decision-making, apply HCD principles in product development, and develop skills in effective user research. They will learn to generate ideas using brainstorming techniques and create prototypes for user testing. By the end, participants will demonstrate proficiency in creating user-centric products validated through testing.

Nov 23rd 2026
5-12 Weeks
Probabilistic Graphical Models 3: Learning (Coursera) Coursera
Stanford University

Probabilistic Graphical Models 3: Learning (Coursera)

Probabilistic graphical models (PGMs) are a rich framework for encoding probability distributions over complex domains: joint (multivariate) distributions over large numbers of random variables that interact with each other. These representations sit at the intersection of statistics and computer science, relying on concepts from probability theory, graph algorithms, machine learning, and more. They are the basis for the state-of-the-art methods in a wide variety of applications, such as medical diagnosis, image understanding, speech recognition, natural language processing, and many, many more. They are also a foundational tool in formulating many machine learning problems.

Nov 23rd 2026
5-12 Weeks
Bioinformatic Methods II (Coursera) Coursera
University of Toronto

Bioinformatic Methods II (Coursera)

Large-scale biology projects such as the sequencing of the human genome and gene expression surveys using RNA-seq, microarrays and other technologies have created a wealth of data for biologists. However, the challenge facing scientists is analyzing and even accessing these data to extract useful information pertaining to the system being studied. This course focuses on employing existing bioinformatic resources – mainly web-based programs and databases – to access the wealth of data to answer questions relevant to the average biologist, and is highly hands-on.

Nov 23rd 2026
5-12 Weeks