what is data science coursera week 2 quiz answers
Data Mining
1. What is an example of a data reduction algorithm?
- Prior Variable Analysis.
- Cojoint Analysis.
- A/B Testing.
- Principal Component Analysis.
2. After the data are appropriately processed, transformed, and stored, what is a good starting point for data mining?
- Non-parametric methods.
- Creating a relational database.
- Data Visualization.
- Machine learning.
3. "Formal evaluation could include testing the predictive capabilities of the models on observed data to see how effective and efficient the algorithms have been in reproducing data." This is known as:
- Overfitting.
- Reverse engineering.
- Prototyping.
- In-sample forecast.
4. In-sample forecast is the process of formally evaluating the predictive capabilities of the models developed using observed data to see how effective the algorithms are in reproducing data.
- True
- False
Regression
6. The author discovered that, all else being equal, houses located less than 5 kms but more than 2.5 kms to shopping centres sold for more than the rest.
- True.
- False.
7. "What are typical land taxes in a house sale?" is a question that can be put to regression analysis.
- False
- True
9. The author discovered that houses located more than 2.5 kms to shopping centres sold for less than the rest.
- False.
- True
10. Who developed the statistical technique known as regression?
- Gerolamo Cardano
- Thomas Bayes
- Blaise Pascal
- Sir Frances Galton
- Sir Isaac Newton
11. Based on the reading, which of the following are questions that can be put to regression analysis?
- Do homes with brick exterior sell in rural areas?
- Do homes with brick exterior sell for less than homes with stone exterior?
- What is the impact of lot size on housing price?
- What are typical land taxes in a house sale?
