This course covers commonly used statistical inference methods for numerical and categorical data. You will learn how to set up and perform hypothesis tests, interpret p-values, and report the results of your analysis in a way that is interpretable for clients or the public. Using numerous data examples, you will learn to report estimates of quantities in a way that expresses the uncertainty of the quantity of interest. You will be guided through installing and using R and RStudio (free statistical software), and will use this software for lab exercises and a final project. The course introduces practical tools for performing data analysis and explores the fundamental concepts necessary to interpret and report results for both categorical and numerical data
Offered By
Inferenzstatistik
Duke UniversityAbout this Course
Flexible deadlines
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Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Beginner Level
Approx. 17 hours to complete
German
Flexible deadlines
Reset deadlines in accordance to your schedule.
Shareable Certificate
Earn a Certificate upon completion
100% online
Start instantly and learn at your own schedule.
Beginner Level
Approx. 17 hours to complete
German
Offered by
Syllabus - What you will learn from this course
20 minutes to complete
Über die Spezialisierung und den Kurs
20 minutes to complete
2 readings
4 hours to complete
Zentraler Grenzwertsatz und Konfidenzintervall
4 hours to complete
7 videos (Total 65 min), 6 readings, 3 quizzes
3 hours to complete
Inferenz und Signifikanz
3 hours to complete
7 videos (Total 59 min), 5 readings, 3 quizzes
4 hours to complete
Inferenz für den Vergleich von Mittelwerten
4 hours to complete
11 videos (Total 84 min), 5 readings, 3 quizzes
4 hours to complete
Inferenz für Anteile
4 hours to complete
11 videos (Total 118 min), 5 readings, 3 quizzes
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