Hypothesis Testing and Significance
Digital Marketing · University of Applied Sciences · Web Analytics
This unit introduces the concepts of hypothesis testing and statistical significance in the context of web analytics. Students will learn how to formulate hypotheses, conduct statistical tests, and interpret the results to make informed decisions based on data.
Zum Üben gibt es 19 Aufgaben. Jede Antwort bekommt sofort eine Rückmeldung, kostenlos und ohne Anmeldung.
Das gehört dazu
- Introduction to Hypothesis Testing
- Statistical Significance
- Types of Hypothesis Tests
- P-values and Decision Making
- Errors in Hypothesis Testing
- Power Analysis
- Confidence Intervals
- Applications of Hypothesis Testing in Web Analytics
Stichworte
- Hypothesis Testing
- P-value
- Null Hypothesis
- Alternative Hypothesis
- Type I Error
- Type II Error
- Web Analytics
Weitere Themen in Web Analytics
- Definition and Importance of Web Analytics
- Types of Web Analytics Data
- Web Analytics Tools and Platforms
- Tracking Codes and Implementation
- Data Accuracy and Sampling
- Data Segmentation and Filtering
- Traffic Metrics: Users, Sessions, and Pageviews
- Engagement Metrics: Bounce Rate, Time on Page, and Scroll Depth