Inferenzstatistik from Coursera

What's inside

Syllabus

Über die Spezialisierung und den Kurs

Dieses kurze Modul führt in die Grundlagen von Coursera-Spezialisierungen und -Kursen im Allgemeinen ein, diese Spezialisierung: Statistik mit R, und diesen Kurs: Inferenzstatistik. Bitte nehmen Sie sich einige Minuten Zeit zum Durchsehen. Vielen Dank für die Teilnahme an diesem Kurs!

Zentraler Grenzwertsatz und Konfidenzintervall

Willkommen bei der Inferenzstatistik! In diesem Kurs werden die Grundlagen der Inferenz erläutert. Sie lesen sich die Lernziele durch, sehen sich die Videos an und bearbeiten schließlich das Quiz und die praktischen Übungen dieser Woche. Neben Videos, in denen neue Konzepte vorgestellt werden, sehen Sie auch einige Videos, in denen Sie Anwendungsbeispiele zu den Themen der Woche sehen. In der ersten Woche werden wir den zentralen Grenzwertsatz (Central Limit Theorem, CLT) und das Konfidenzintervall vorstellen.

Inferenz und Signifikanz

Willkommen in der 2. Woche! In dieser Woche werden wir formale Hypothesentests besprechen und die Testverfahren mit Hilfe von Konfidenzintervallen in Beziehung zu Schätzungen setzen. Diese Themen werden im Zusammenhang mit der Arbeit mit einem Mittelwert der Grundgesamtheit eingeführt, aber wir geben Ihnen auch einen kurzen Einblick in das, was in den nächsten zwei Wochen kommen wird, indem wir besprechen, wie die Methoden, die wir lernen, auf andere Schätzwerte ausgeweitet werden können. Wir werden auch wichtige Überlegungen wie Entscheidungsfehler und statistische vs. praktische Signifikanz erörtern. In den Übungen dieser Woche werden die Konzepte der Stichprobenverteilungen und Konfidenzniveaus veranschaulicht.

Inferenz für den Vergleich von Mittelwerten

Willkommen in der 3. Woche des Kurses! Diese Woche werden wir die t-Verteilung und den Vergleich von Mittelwerten sowie eine simulationsbasierte Methode zur Erstellung eines Konfidenzintervalls vorstellen: das Bootstrapping. Wenn Sie Fragen haben oder Diskussionen führen möchten, nutzen Sie bitte das Forum für diese Woche, um Ihre Fragen zu stellen oder mit Gleichgesinnten zu diskutieren.

Inferenz für Anteile

Willkommen bei der vierten Woche unseres Kurses! In dieser Einheit werden wir die Inferenz für kategoriale Daten erörtern. Wir verwenden die in dieser Woche vorgestellten Methoden, um Fragen wie "Welcher Anteil der amerikanischen Öffentlichkeit ist mit der Arbeit des Obersten Gerichtshofs einverstanden?" zu beantworten.

Datenanalyse-Projekt

In dieser Woche werden Sie die zur Verfügung gestellte Datenbasis verwenden, um eine Frage zur Datenanalyse zu beantworten und darüber zu berichten. Bitte lesen Sie die Hintergrundinformationen, sehen Sie sich die Berichtsvorlage an (die Sie über den Link in der Lektion "Informationen zum Projekt" herunterladen können), und bearbeiten Sie dann die Peer-Review-Aufgabe.

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Teaches the fundamental concepts needed for interpreting and reporting results in data analysis

Develops practical tools and skills for statistical data analysis using R and RStudio

Led by experts in the field, Mine Çetinkaya-Rundel

Facilitates peer learning and networking through the discussion forum

Requires prior familiarity with statistics concepts and a willingness to engage in mathematical reasoning

May not be suitable for learners seeking a comprehensive foundation in statistics

Career center

Learners who complete Inferenzstatistik will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists use scientific methods to extract knowledge and insights from data, often using statistical techniques. Inferential statistics are essential for this role, as they enable Data Scientists to draw conclusions and make predictions based on data. This course provides a strong foundation in inferential statistics, covering topics such as hypothesis testing and confidence intervals, which are essential for success in this field.

See salaries and explore the career path for Data Scientist

Market Researcher

Market Researchers gather and analyze data on consumer trends and preferences to help businesses develop and improve their products and services. Statistical methods are essential for Market Researchers to understand the significance of their findings and make accurate predictions. This course provides a strong foundation in inferential statistics, which will enable you to interpret data and draw meaningful conclusions.

See salaries and explore the career path for Market Researcher

Data Analyst

Data Analysts are responsible for collecting, cleaning, and analyzing data to help businesses make informed decisions. This course can help you gain foundational knowledge in statistical methods, which are crucial for data analysis. The course covers topics like hypothesis testing, confidence intervals, and data visualization, which are essential skills for Data Analysts.

See salaries and explore the career path for Data Analyst

Quantitative Analyst

Quantitative Analysts use statistical and mathematical modeling to assess risk and make investment decisions in the financial industry. This course will equip you with the statistical skills required for this role, including hypothesis testing and confidence interval estimation. Understanding the concepts covered in this course will give you a competitive edge in the highly quantitative field of Finance.

See salaries and explore the career path for Quantitative Analyst

Biostatistician

Biostatisticians apply statistical methods to the field of medicine and healthcare. They analyze medical data to evaluate the effectiveness of treatments and make informed decisions about patient care. This course provides a strong foundation in statistical inference, which is essential for Biostatisticians to draw valid conclusions from medical data. The course covers topics such as hypothesis testing, confidence intervals, and regression analysis, which are widely used in medical research.

See salaries and explore the career path for Biostatistician

Epidemiologist

Epidemiologists investigate the causes and patterns of diseases in populations. Statistical methods are essential for Epidemiologists to analyze data and draw conclusions about the prevalence and transmission of diseases. This course provides a strong foundation in statistical inference, which is essential for Epidemiologists to conduct valid research and make evidence-based recommendations for public health policy.

See salaries and explore the career path for Epidemiologist

Survey Researcher

Survey Researchers design and conduct surveys to collect data on public opinion and behavior. Statistical methods are essential for Survey Researchers to analyze data and draw conclusions about the population. This course will provide you with a strong foundation in inferential statistics, covering topics such as hypothesis testing and confidence intervals, which are essential for designing and analyzing surveys.

See salaries and explore the career path for Survey Researcher

UX Researcher

UX Researchers study user behavior and preferences to improve the design and usability of products and services. Statistical methods are essential for UX Researchers to analyze data and draw conclusions about user experiences. This course provides a strong foundation in inferential statistics, which will enable you to interpret data and make informed recommendations for product design and development.

See salaries and explore the career path for UX Researcher

Actuary

Actuaries assess risk and uncertainty in the insurance and finance industries. Statistical methods are essential for Actuaries to evaluate the likelihood of future events and make informed decisions about risk management. This course provides a strong foundation in inferential statistics, covering topics such as hypothesis testing and confidence intervals, which are essential for Actuaries to accurately assess risk and make sound financial decisions.

See salaries and explore the career path for Actuary

Operations Research Analyst

Operations Research Analysts use mathematical and statistical models to optimize business processes and systems. Statistical methods are essential for Operations Research Analysts to analyze data and make recommendations for improvement. This course provides a strong foundation in inferential statistics, which is essential for Operations Research Analysts to make data-driven decisions and improve organizational efficiency.

See salaries and explore the career path for Operations Research Analyst

Business Analyst

Business Analysts use data to identify and solve business problems. Statistical methods are essential for Business Analysts to analyze data and make recommendations for improvement. This course provides a strong foundation in inferential statistics, which is essential for Business Analysts to make data-driven decisions and improve business outcomes.

See salaries and explore the career path for Business Analyst

Statistician

Statisticians collect, analyze, and interpret data to provide insights and make informed decisions. Statistical methods are essential for Statisticians to draw valid conclusions from data. This course provides a strong foundation in inferential statistics, covering topics such as hypothesis testing and confidence intervals, which are essential for Statisticians to conduct accurate research and make evidence-based recommendations.

See salaries and explore the career path for Statistician

Data Engineer

Data Engineers design, build, and maintain data systems and infrastructure. Statistical methods may be useful for Data Engineers to understand the data they are working with and to build systems that can handle and process data efficiently. This course provides a foundation in statistical concepts and methods, which can be helpful for Data Engineers to perform data analysis and quality control.

See salaries and explore the career path for Data Engineer

Product Manager

Product Managers are responsible for the development and launch of new products and features. Statistical methods may be useful for Product Managers to understand the needs of their customers and to evaluate the success of their products. This course provides a foundation in statistical concepts and methods, which can be helpful for Product Managers to make data-driven decisions about product development and marketing.

See salaries and explore the career path for Product Manager

Software Engineer

Software Engineers design, develop, and maintain software systems. Statistical methods may be useful for Software Engineers to understand the performance and reliability of their software. This course provides a foundation in statistical concepts and methods, which can be helpful for Software Engineers to perform data analysis and make informed decisions about software design and development.

See salaries and explore the career path for Software Engineer

Inferenzstatistik

What's inside

Syllabus

Good to know

Save this course

Activities

Career center

Reading list

Share

Similar courses