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Project overview
In this project, you’ll take on the role of a Jeopardy contestant looking to gain an edge by analyzing patterns in past questions. Using a dataset of 20,000 questions, you’ll apply chi-squared tests and text analysis techniques in R to uncover which categories come up most often and which topics are associated with high-value clues.
This project allows you to hone your skills in hypothesis testing and string manipulation while developing data-driven strategies for a real-world scenario. You’ll clean and normalize text data, test hypotheses about category frequency, and identify terms associated with high-value questions. These techniques can be applied to a wide range of text analysis problems.
Objective: Use chi-squared tests and text analysis in R to identify patterns in Jeopardy questions and develop optimal game strategies.
Key skill required
To complete this project, it's recommended to build these foundational skills in R
- Understanding probability distributions
- Identifying key hypothesis testing concepts
- Applying the chi-squared test to categorical data
- Extending the chi-squared test to multiple categories
Projects steps
Step 1: Getting To Know Jeopardy Data
Step 2: Fixing Data Types
Step 3: Normalizing Text
Step 4: Making Dates More Accessible
Step 5: Focusing On Particular Subject Areas
Step 6: Unique Terms In Questions
Step 7: Terms In Low and High Value Questions
Step 8: Next steps
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