In most areas of health, data is being used to make important decisions. As a health population manager, you will have the opportunity to use data to answer interesting questions. In this course, we will discuss data analysis from a responsible perspective, which will help you to extract useful information from data and enlarge your knowledge about specific aspects of interest of the population.
Population Health: Responsible Data Analysis
von
Population Health: Responsible Data Analysis
Universiteit Leiden
Über diesen Kurs
5,053 kürzliche Aufrufe
Was Sie lernen werden
Knows (the value of) all aspects of data management and acknowledge the importance of initial data analysis.
Knows the pros and cons of statistical methods and can choose the appropriate data analysis approach in common health related problems.
Is able to interpret statistical results and to draw responsible conclusions.
Kompetenzen, die Sie erwerben
R ProgrammingData AnalysisRegression AnalysisData ReportingStatistical Data
100 % online
Beginnen Sie sofort und lernen Sie in Ihrem eigenen Tempo.
Flexible Fristen
Setzen Sie Fristen gemäß Ihrem Zeitplan zurück.
Stufe „Anfänger“
No previous statistical knowledge is needed, just basic mathematical skills.
Ca. 23 Stunden zum Abschließen
Empfohlen: 11 hours/week
Englisch
Untertitel: Englisch
Lehrplan - Was Sie in diesem Kurs lernen werden
2 Stunden zum Abschließen
Welcome to Responsible Data Analysis
Welcome to the course Responsible Data Analysis! You’re joining thousands of learners currently enrolled in the course. I'm excited to have you in class and look forward to your contributions to the learning community.To begin, I recommend taking a few minutes to explore the course site. Review the material we’ll cover each week, and preview the assignments you’ll need to complete to pass the course. Click Discussions to see forums where you can discuss the course material with fellow students taking the class. If you have questions about course content, please post them in the forums to get help from others in the course community. For technical problems with the Coursera platform, visit the Learner Help Center. Good luck as you get started, and I hope you enjoy the course!
2 Stunden zum Abschließen
2 Videos (Gesamt 4 min), 6 Lektüren
6 Lektüren
Meet the instructors & the team10m
Leiden University: Facts & Figures10m
About this Course10m
Glossary10m
Community Guidelines 5m
What is your learning path?5m
4 Stunden zum Abschließen
From Individuals to Data
In this module, we will discuss how to obtain, store, clean and explore the data necessary to answer your research question. First, we will see how to collect data of good quality. Second, we will see how to address privacy and security when dealing with personal data. Then, we will see how to first describe and summarize your data. Finally, we will discuss the principles of initial data analysis.
4 Stunden zum Abschließen
6 Videos (Gesamt 33 min), 4 Lektüren, 6 Quiz
6 Videos
Structured data collection6m
Data privacy and security8m
Data description8m
Initial data analysis7m
To conclude1m
4 Lektüren
Structured data collection in practice30m
Privacy and security in practice15m
Case Study: Descriptive Statistics40m
Case study: Initial data analysis in practice20m
6 praktische Übungen
Practice quiz20m
Practice Quiz20m
R exercise15m
R exercise: Initial data analysis30m
Reflect on your goals10m
Test your knowledge20m
4 Stunden zum Abschließen
From data to information I: statistical inference
In this module, we will see how to deal with data obtained from a limited number of individuals. You will discover how statistical inference can make the connection between samples and populations. First, we will discuss important concepts such as random variation, sampling distribution and standard error. Second, we will discuss the principles of hypothesis testing. Then, we will review the moist commonly used statistical tests. Finally, we will discuss how to decide how large your study sample should be.
4 Stunden zum Abschließen
6 Videos (Gesamt 37 min), 4 Lektüren, 6 Quiz
6 Videos
Statistical Inference9m
Fundamentals of hypothesis testing7m
Choosing the right statistical test8m
Sample size calculation7m
To conclude1m
4 Lektüren
Confidence intervals in practice20m
Relation between p-values and confidence intervals30m
Hypothesis testing in practice25m
Case study: Sample size calculation in practice30m
6 praktische Übungen
Practice quiz statistical interference20m
Practice quiz hypothesis testing15m
Practice quiz: Which test?15m
Practice quiz: Sample size15m
Reflect on your goals10m
Test your knowledge20m
5 Stunden zum Abschließen
From data to information II: regression techniques
In this module, we will discuss the basic principles of regression modeling, a collection of powerful tools to analyze complex data. We will start simple, and increase the complexity of the models step by step. We will start with linear regression, used with continuous outcomes. Then we will continue with logistic regression, which can be used to model binary variables, and finally we will consider regression with time to event outcomes.
5 Stunden zum Abschließen
6 Videos (Gesamt 36 min), 5 Lektüren, 6 Quiz
6 Videos
Simple linear regression8m
Multiple linear regression7m
Logistic regression7m
Cox proportional hazards regression9m
To conclude1m
5 Lektüren
Case study: Simple linear regression in practice30m
Dealing with binary explanatory variables
Case study: Multiple linear regression in practice15m
Case study: Logistic regression in practice25m
Case study: Cox proportional hazards regression in practice30m
6 praktische Übungen
R - exercise: Simple linear regression15m
R exercise: Multiple linear regression30m
R exercise: Logistic regression30m
R-exercise: Cox proportional hazards regression30m
Reflect on your goals10m
Test your knowledge20m
6 Stunden zum Abschließen
From information to knowledge
In this module , we will cover the critical assessment of data analysis results, and we will discuss challenges and dangers of data analysis in the era of big data and massive amounts of information. First, we will see how bad data analysis practice can dramatically impact scientific progress. Second, we will address the hot topic of how to report uncertainty in scientific findings. This has been object of big controversy in the scientific literature. We invited two experts to present their different points of view. Then, we will discuss different forms of bias. Finally, we will give you tips and tricks to write a perfect statistical plan.
6 Stunden zum Abschließen
7 Videos (Gesamt 41 min), 4 Lektüren, 4 Quiz
7 Videos
Are most research findings false?8m
Interview12m
Data alone does not tell the whole story7m
Good statistical practice7m
To conclude1m
Course Conclusion56
4 Lektüren
The Likelihood of Irreproducible Research45m
Abandoning p-values?30m
Understanding Simpson's paradox15m
Why do we need to plan ahead?30m
4 praktische Übungen
Practice quiz20m
Reflect on your goals10m
Test your knowledge30m
Final assessment1h 30m
Bewertungen
Top-Bewertungen von POPULATION HEALTH: RESPONSIBLE DATA ANALYSIS
von TASep 27, 2019
To research and review the data Population Health: Responsible Data Analysis is mostly perfect to me as a humanitarian.
von GAOct 6, 2019
Had much fun during this course. Hope more programmes like this in future are offered for free.
Über Universiteit Leiden
Leiden University is one of Europe's foremost research universities. This prominent position gives our graduates a leading edge and prepares them for careers both within and outside of academia. Leiden University is the oldest university in the Netherlands, founded in 1575. Our motto is: Praesidium Libertatis (Bastion of Liberty) - Freedom of spirit, thought and expression. Leiden University has a campus in Leiden and The Hague, with 7 faculties, 47 Bachelor Programmes, 79 Master Programmes and nearly 30,000 students.
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