Join Chris DallaVilla for an in-depth discussion in this video Pros and cons, part of The Data Science of Marketing.
powerful is maybe the wrong word…but they both offer a larger range of data science options…and capabilities for statistical modeling…when compared to Tableau.…I'm not sure what the statistics are for R's usage…compared to that of Python…but I would guess R experiences a line share.…It's just a statistical modeling powerhouse.…And there's a very robust community creating…and maintaining open source packages.…R is great for addressing most data analysis needs…
In this course, discover how to gain valuable insights from large data sets using specific languages and tools. Follow Chris DallaVilla as he walks through how to use R, Python, and Tableau to perform data modeling and assess performance. As Chris dives into these concepts, he shares specific case studies that come directly from his own work with clients. Plus, he shares three essential—and practical—best practices for data-driven marketing that you can use to bolster your organization's marketing performance.
- Installing R, Python, and Tableau
- Navigating the UI for R, Python, and Tableau
- Using R, Python, and Tableau
- Exploratory analysis
- Performing regression analysis
- Performing a cluster analysis
- Performing a conjoint assessment
- Stakeholder alignment
Skill Level Intermediate
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1. Software Installation
2. Data, Exploratory Analysis, and Performance Analysis
3. Inference and Regression Analysis
5. Cluster Analysis
6. Conjoint Analysis
7. Best Practices
Next steps1m 8s
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