Learn how to perform a conjoint assessment using Tableau and how to interpret the results.
- [Instructor] So we did a little multiple regression magic…in our previous video, using Python,…and I like how that brings the technical components…of our course back to where we started from…and really helps you to build on those skills…that you learned to perform regression analysis.…Tableau makes this process relatively easy as well.…So we have the platform open…and we've connected to our exercise data for a case study,…and we'll navigate into our workspace…by selecting Sheet 1.…So this goes back to the fundamentals we learned…in the regression chapter.…
We need to assign the measures for our dependent variables.…Which one do you think that is?…If you said rating, you got it right.…Let's go ahead and drop our Rating measure on our Row shelf.…And again, we're looking at multiple independent…variables here, I would just select the whole batch of them…and drop them on our Column shelf.…Now we'll turn off our aggregate measures…from the Analysis menu.…And then we'll apply the trend line.…
So back into that Analysis menu, Trend Lines,…
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
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