regression analysis: simplify complex data relationships coursera weekly challenges 5 answers
Test your knowledge: Foundations of logistic regression
1. When building a logistic regression model, what does CLF stand for?
- Connector
- Classifier
- Claimer
- Codifier
2. Which package do you use to create a plot of your model to visualize its results?
- Results package
- Matrix package
- Dashboard package
- Seaborn package
Test your knowledge: Logistics regression with Python
3. No extreme outliers is one of the four main binomial logistic regression assumptions. What are the other three? Select all that apply.
- Linearity
- No multicollinearity
- Independent observations
- Homoscedasticity
5. Fill in the blank: The maximum likelihood estimation is a technique used for estimating the beta parameters that _____ the likelihood of a model producing the observed data.
- reduce
- maximize
- balance
- control
Test your knowledge: Interpret logistic regression results
6. The confusion matrix is a graphical representation of how accurate a classifier is at predicting what for a categorical variable?
- Precision
- Errors
- Labels
- Validity
7. Fill in the blank: _____ measures the proportion of positive predictions that were true positives.
- Validity
- Precision
- Accuracy
- Recall
8. Which of the following provide additional information about the likelihood of a result being merely by chance? Select all that apply.
- P-value
- Maximum likelihood estimation
- Confidence intervals
- Logit
Shuffle Q/A 1
Test your knowledge: Compare regression models
9. Which model might a data professional consider first if the outcome variable is binary?
- Single linear regression
- Hypothesis testing
- Multiple linear regression
- Binomial logistic regression
10. A data professional can use recall to evaluate a logistic regression model. What other metrics can be used to meet this goal? Select all that apply.
- Precision
- R squared
- P-value
- Confusion matrices
