Learn how to perform analysis for prediction using R and how to interpret the results.
- [Instructor] So we have our RStudio open…and I have already connected to the data.…For reference, we are using the exercise files…in the directory 04_02, now let's go ahead and…run that line so we can bring our data in.…And I want to open up our data for a moment…so I'm just going to double click.…I want to point out that we had this sales…classification column and what I know about this…column, just to reveal what we're working with here…is that our data has been encoded.…
So in other words, during the data preparation…process, this data was categorized into these three buckets,…A, B, and C, A is the highest performer,…B is in the middle and C is the lowest performer.…So let's go ahead and close out of our data.…Let me see our code again, and I want…to see how many of our client's stores…are operating at these different levels.…So I'm going to bring up a synopsis of that data…using the table command so we'll type that like…this, I'll type table, I'll then apply our variable…for our data frame, my prediction data.…
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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