Einführung in Zeitreihenanalyse mit R from Coursera

In diesem zweistündigen Projekt wirst du eine gründliche Analyse einer Zeitreihe mithilfe eines ARIMA-Modells durchführen. Dieses Projekt erklärt die grundlegenden Konzepte von Zeitreihenanalyse und illustriert dies praktisch in RStudio. Wir beschreiben die Arten von Zeitreihen und ihre verschiedenen Komponenten. Das Projekt deckt ab, wie man diagnostische Tests durchführt, um die grundlegenden Vorraussetzungen für ARIMA-Modelle zu testen. Schließlich leiten wir das beste Modell ab, um zukünftige Werte vorherzusagen. Wir werden gemeinsam die grundlegenden Pakete und Funktionen in R durchgehen, um Zeitreihenanalyse einfach zu machen. Du benötigst für dieses Projekt keine Vorkenntnisse! Wir werden alles Schritt für Schritt erklären.

Am Ende dieses Projektes wirst du in der Lage sein, eine Zeitreihe systematisch zu analysieren, die Vorraussetzungen für ein ARIMA-Modell zu prüfen, eine Zeitreihe mithilfe eines passenden ARIMA-Modells zu modellieren und daraus zukünftige Werte vorherzusagen.

What's inside

Syllabus

Projekt-Überblick

Good to know

Know what's good

, what to watch for

, and possible dealbreakers

Geeignet für Anfänger ohne Vorkenntnisse in Zeitreihenanalyse

Vermittelt grundlegende Konzepte der Zeitreihenanalyse, die in vielen Branchen Anwendung finden

Anhand praktischer Beispiele in RStudio werden die Konzepte veranschaulicht

Umfasst sowohl Theorie als auch Anwendung und ermöglicht so ein umfassendes Verständnis

Bietet die Möglichkeit, eigene Zeitreihen zu analysieren und Modelle zu erstellen

Kursdauer von nur zwei Stunden, was für Berufstätige und Studierende mit wenig Zeit geeignet ist

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 Einführung in Zeitreihenanalyse mit R with these activities:

Üben Sie die Verwendung von ARIMA-Modellen in RStudio

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Vertiefen Sie Ihr Verständnis, indem Sie praktische Beispiele in einer realen Umgebung ausführen.

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Installieren Sie die erforderlichen Pakete in RStudio
Importieren Sie einen Zeitreihen-Datensatz
Erstellen Sie ein ARIMA-Modell
Überprüfen Sie die Modellanpassung
Prognostizieren Sie zukünftige Werte

Tragen Sie zu einem Open-Source-Projekt zur Zeitreihenanalyse bei

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Erweitern Sie Ihr Wissen und vernetzen Sie sich mit Experten auf dem Gebiet.

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Identifizieren Sie ein relevantes Open-Source-Projekt
Überprüfen Sie den Code und identifizieren Sie Möglichkeiten für Beiträge
Schreiben Sie Code oder verbessern Sie die Dokumentation
Senden Sie Ihre Beiträge zur Überprüfung
Interagieren Sie mit anderen Mitwirkenden und lernen Sie aus ihren Erfahrungen

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Career center

Learners who complete Einführung in Zeitreihenanalyse mit R will develop knowledge and skills that may be useful to these careers:

Data Scientist

Data Scientists use advanced statistical algorithms to model and analyze data sets. They often collaborate with business leaders to determine how this data can be used for strategic planning. This course may be useful for a Data Scientist who works with time series data. Specifically, it can assist in developing time series models with R.

See salaries and explore the career path for Data Scientist

Machine Learning Engineer

Machine Learning Engineers build and maintain machine learning models. This course could be useful for Machine Learning Engineers who work with time series data. It provides a foundation in time series analysis and teaches how to use R to build ARIMA models.

See salaries and explore the career path for Machine Learning Engineer

Business Analyst

Business Analysts use data and analysis to help businesses make informed decisions. This course could be useful for Business Analysts who work with time series data. It provides an introduction to time series analysis and demonstrates how to use R to build ARIMA models.

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Operations Research Analyst

Operations Research Analysts use mathematical and analytical techniques to solve business problems and improve efficiency. This course could be useful for Operations Research Analysts who work with time series data. It covers how to use R to build ARIMA models.

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Statistician

Statisticians collect, analyze, interpret, and present data to help businesses and organizations make informed decisions. This course may be useful for Statisticians who want to learn how to use time series analysis to model and forecast data.

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Software Engineer

Software Engineers design, develop, and maintain software systems. This course could be useful for Software Engineers who work with time series data. It provides a foundation in time series analysis and teaches how to use R to build ARIMA models.

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Data Analyst

Data Analysts translate raw data into formats that can be understood by organizational stakeholders. They build data models that help organizations make informed decisions. This course may be helpful for Data Analysts on teams that work with time series data. Namely, it can help build a foundation in how to model and forecast data.

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Financial Analyst

Financial Analysts use financial data and models to help investors make informed decisions. This course could be useful for Financial Analysts looking to enhance their time series modeling skills, as it covers how to build ARIMA models in R.

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Data Engineer

Data Engineers design, build, and maintain data pipelines and infrastructure. This course may be useful for Data Engineers who work with time series data. It provides a foundation in time series analysis and teaches how to use R to build ARIMA models.

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Quantitative Analyst

Quantitative Analyst use mathematical and statistical models to find investment opportunities and assess the risk of financial products. This course may be helpful for Quantitative Analysts who work with time series data. In particular, it can help build a foundation in ARIMA modeling.

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Actuary

Actuaries assess the financial impact of risk and uncertainty. This course may be helpful for Actuaries who want to strengthen their skills in time series analysis. In particular, it covers how to use ARIMA models in R.

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Economist

Economists study the production, distribution, and consumption of goods and services. This course may be useful for Economists who want to learn how to use time series analysis to forecast economic trends.

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Market Researcher

Market Researchers analyze market trends and consumer behavior to help businesses make informed decisions about product development and marketing strategies. This course may be useful for Market Researchers who want to learn how to use time series analysis to forecast future trends.

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Data Science Manager

Data Science Managers lead teams of data scientists and oversee data science projects. This course may be useful for aspiring Data Science Managers who want to build a stronger foundation in time series analysis. It covers the basics of time series analysis and demonstrates how to use R to build ARIMA models.

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Quantitative Risk Analyst

Quantitative Risk Analysts use mathematical and statistical models to assess and manage financial risk. This course may be useful for Quantitative Risk Analysts who want to enhance their skills in time series analysis. In particular, it teaches how to use ARIMA models in R.

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Einführung in Zeitreihenanalyse mit R

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