Introducción a Ciencia de Datos en Salud from edX

En el campo de las ciencias de la salud se genera una gran cantidad de datos que son la base para tomar decisiones al administrar instituciones y sistemas de salud, al momento de dar atención a un paciente, así como en el estudio de la calidad del servicio.

Lo anterior origina la necesidad de que casi cualquier colaborador del sector salud, ya sean profesionistas, administradores e investigadores aprendan a clasificar, describir e interpretar datos y evidencias científicas, aplicando las pruebas estadísticas adecuadas.

Por dicha razón, en este curso te brindaremos las herramientas para que seas capaz de reconocer, analizar, interpretar, visualizar y utilizar de forma efectiva los datos generados en las ciencias de la salud, así como describir una base de datos empleando la estadística descriptiva (medidas de tendencia central, de dispersión). ¡Inscríbete!

What you'll learn

Clasificar apropiadamente los datos de salud.
Identificar pruebas de estadística descriptiva para datos cuantitativos y cualitativos.
Generar una base de datos de salud en Excel.
Ejecutar efectivamente las pruebas de estadística descriptiva [medidas de tendencia central, dispersión y posición].
Representar los datos descriptivos de una investigación.
Reconocer la descripción de resultados en la evidencia científica.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Well-suited for nearly any collaborator within healthcare systems, who must analyze data and scientific evidence

This course will develop your ability to visualize and interpret data effectively

In this course, you will learn to apply appropriate statistical descriptive tests for both quantitative and qualitative data

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 Introducción a Ciencia de Datos en Salud with these activities:

Read 'Introduction to Statistical Thinking' by Benjamin Yakir

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Gain a comprehensive understanding of statistical concepts and their applications in various fields, providing a solid foundation for the course.

View Introduction to Statistical Thinking on Amazon

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Read through the book, taking notes on key concepts and examples.
Complete the exercises and practice problems provided in the book.

Brush up on basic statistics

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Reinforce your understanding of basic statistical concepts and techniques, making it easier to grasp more advanced topics covered in the course.

Browse courses on Inferential Statistics

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Review notes or textbooks on descriptive statistics and inferential statistics.
Practice solving problems related to central tendency, dispersion, and hypothesis testing.

Participate in peer discussion groups

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Engage with peers to share knowledge, clarify concepts, and gain diverse perspectives on statistical concepts.

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Join online forums or discussion groups related to the course topics.
Actively participate in discussions, asking and answering questions.
Collaborate with peers on projects or assignments.

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Follow tutorials on data analysis techniques

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Gain hands-on experience in applying statistical techniques to real-world datasets, deepening your understanding of their practical applications.

Browse courses on Data Analysis

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Identify online tutorials or courses on data analysis techniques relevant to the course.
Follow the tutorials step-by-step, working through examples and exercises.
Apply the techniques learned to analyze a small dataset of your own.

Solve practice problems on statistical tests

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Enhance your problem-solving skills and strengthen your understanding of the different statistical tests covered in the course.

Browse courses on Hypothesis Testing

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Find practice problems or online quizzes on statistical tests.
Attempt the problems and check your answers against provided solutions.
Identify areas where you need further practice and focus on those concepts.

Contribute to an open-source statistical software project

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Gain hands-on experience in the development and application of statistical software, enhancing your technical skills and contributing to the open-source community.

Browse courses on Open Source

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Identify an open-source statistical software project that aligns with your interests.
熟悉项目文档和代码库。
Identify a bug or feature that you can contribute to.
Implement the fix or feature and submit a pull request.

Create a data visualization dashboard

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Develop your data visualization skills by creating an interactive dashboard that communicates statistical insights effectively.

Browse courses on Data Visualization

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Choose a relevant dataset and identify the key insights you want to convey.
Select appropriate visualization techniques and tools to create the dashboard.
Design and implement the dashboard, ensuring it is user-friendly and informative.

Develop a statistical model for a real-world problem

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Apply your statistical knowledge to solve a real-world problem, putting your skills into practice and developing a deeper understanding of the subject matter.

Browse courses on Statistical Modeling

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Identify a problem that can be addressed using statistical modeling.
Collect and clean the necessary data.
Develop and train a statistical model using appropriate techniques.
Evaluate the performance of the model and make adjustments as needed.
Present your findings and insights.

Career center

Learners who complete Introducción a Ciencia de Datos en Salud will develop knowledge and skills that may be useful to these careers:

Statistician

A Statistician collects, analyzes, interprets, and presents data. They use statistical methods to develop models, test hypotheses, and make predictions. This course would be beneficial for aspiring Statisticians, as it provides a strong foundation in statistical analysis and interpretation. The course covers topics such as data classification, statistical tests, and data visualization, which are all essential skills for a Statistician.

See salaries and explore the career path for Statistician

Data Scientist

A Data Scientist uses scientific methods, processes, algorithms, and systems to extract knowledge and insights from data in various forms, both structured and unstructured. This course would provide a foundation in data analysis and interpretation, which are essential skills for a Data Scientist. The course covers topics such as data classification, statistical analysis, data visualization, and hypothesis testing, all of which are relevant to the field of data science.

See salaries and explore the career path for Data Scientist

Epidemiologist

An Epidemiologist investigates the distribution and patterns of health events and diseases in a population. They use their findings to develop and implement public health programs. This course would be helpful for aspiring Epidemiologists, as it provides a foundation in data analysis and interpretation. The course covers topics such as data classification, statistical analysis, and data visualization, which are all relevant to the field of epidemiology.

See salaries and explore the career path for Epidemiologist

Medical Researcher

A Medical Researcher designs and conducts studies to investigate the causes and treatments of diseases. They use data to analyze results and draw conclusions. This course would be helpful for aspiring Medical Researchers, as it provides a foundation in data analysis and interpretation. The course covers topics such as data classification, statistical analysis, and data visualization, which are all relevant to the field of medical research.

See salaries and explore the career path for Medical Researcher

Health Informatics Specialist

A Health Informatics Specialist uses data to improve the quality and efficiency of healthcare delivery. This course would provide a foundation in data analysis and interpretation, which are essential skills for a Health Informatics Specialist. The course covers topics such as data classification, statistical analysis, and data visualization, all of which are relevant to the field of health informatics.

See salaries and explore the career path for Health Informatics Specialist

Clinical Data Manager

A Clinical Data Manager is responsible for the collection, management, and analysis of clinical data. This course would provide a foundation in data analysis and interpretation, which are essential skills for a Clinical Data Manager. The course covers topics such as data classification, statistical analysis, and data visualization, all of which are relevant to the field of clinical data management.

See salaries and explore the career path for Clinical Data Manager

Health Policy Analyst

A Health Policy Analyst analyzes and interprets data to develop and evaluate health policies. They use their findings to make recommendations to policymakers. This course would be beneficial for aspiring Health Policy Analysts, as it provides a foundation in data analysis and interpretation. The course covers topics such as data classification, statistical analysis, and data visualization, which are all relevant to the field of health policy analysis.

See salaries and explore the career path for Health Policy Analyst

Quality Improvement Specialist

A Quality Improvement Specialist develops and implements programs to improve the quality of healthcare services. They use data to track progress and identify areas for improvement. This course would be beneficial for aspiring Quality Improvement Specialists, as it provides a foundation in data analysis and interpretation. The course covers topics such as data classification, statistical analysis, and data visualization, which are all relevant to the field of quality improvement.

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Data Analyst

A Data Analyst collects, cleans, and analyzes data to identify trends and patterns. They use their findings to make recommendations and improve business outcomes. This course would be useful for aspiring Data Analysts, as it provides a foundation in data analysis and interpretation. The course covers topics such as data classification, statistical analysis, and data visualization, which are all relevant to the field of data analytics.

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Nurse

A Nurse provides care to patients in a variety of settings. They use data to monitor patient outcomes and identify potential health problems. This course would be useful for aspiring Nurses, as it provides a foundation in data analysis and interpretation. The course covers topics such as data classification, statistical analysis, and data visualization, which are all relevant to the field of nursing.

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Physician Assistant

A Physician Assistant provides medical care under the supervision of a physician. They use data to make decisions about patient care and monitor patient outcomes. This course would be useful for aspiring Physician Assistants, as it provides a foundation in data analysis and interpretation. The course covers topics such as data classification, statistical analysis, and data visualization, which are all relevant to the field of medicine.

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Public Health Educator

A Public Health Educator develops and implements programs to promote health and prevent disease. They use data to evaluate the effectiveness of their programs. This course would be useful for aspiring Public Health Educators, as it provides a foundation in data analysis and interpretation. The course covers topics such as data classification, statistical analysis, and data visualization, which are all relevant to the field of public health education.

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Risk Manager

A Risk Manager identifies and assesses risks to an organization. They use data to develop and implement risk management plans. This course would be useful for aspiring Risk Managers, as it provides a foundation in data analysis and interpretation. The course covers topics such as data classification, statistical analysis, and data visualization, which are all relevant to the field of risk management.

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Healthcare Administrator

A Healthcare Administrator plans, directs, and coordinates the provision of healthcare services. They use data to make decisions about resource allocation, staffing, and quality of care. This course would be useful for aspiring Healthcare Administrators, as it provides a foundation in data analysis and interpretation. The course covers topics such as data classification, statistical analysis, and data visualization, which are all relevant to the field of healthcare administration.

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Pharmacist

A Pharmacist dispenses medications and provides advice on their use. They also use data to monitor patient outcomes and identify potential drug interactions. This course would be useful for aspiring Pharmacists, as it provides a foundation in data analysis and interpretation. The course covers topics such as data classification, statistical analysis, and data visualization, which are all relevant to the field of pharmacy.

See salaries and explore the career path for Pharmacist