Podcast
Questions and Answers
What is one challenge in establishing causality between a car's age and its sale price?
What is one challenge in establishing causality between a car's age and its sale price?
Controlling for all other factors
In what scenario would we need to compare the sale prices of two identical cars with one being older than the other?
In what scenario would we need to compare the sale prices of two identical cars with one being older than the other?
To establish causality between age and sale price
What distribution is assumed for the 'Sale Price' of cars in the dataset discussed?
What distribution is assumed for the 'Sale Price' of cars in the dataset discussed?
Normal distribution
What is the mean sale price (μ) assumed in the normal distribution of car sale prices?
What is the mean sale price (μ) assumed in the normal distribution of car sale prices?
Within how many standard deviations do about 68% of all car sale prices fall from the mean?
Within how many standard deviations do about 68% of all car sale prices fall from the mean?
What is the range within which about 95% of all car sale prices fall from the mean?
What is the range within which about 95% of all car sale prices fall from the mean?
What theorem states that the distribution of sample means will approximate a normal distribution?
What theorem states that the distribution of sample means will approximate a normal distribution?
How many car sale prices are sampled to calculate the mean sale price in the Central Limit Theorem scenario?
How many car sale prices are sampled to calculate the mean sale price in the Central Limit Theorem scenario?
Explain how Bayesian Statistics can be used to update beliefs about the mean Credit Score of customers who defaulted.
Explain how Bayesian Statistics can be used to update beliefs about the mean Credit Score of customers who defaulted.
Describe the purpose of Survival Analysis in predicting customer default probability.
Describe the purpose of Survival Analysis in predicting customer default probability.
Explain how Time Series Analysis can help identify patterns in default rates.
Explain how Time Series Analysis can help identify patterns in default rates.
How does Principal Component Analysis (PCA) relate Age, Annual Income, and Credit Score in identifying variance?
How does Principal Component Analysis (PCA) relate Age, Annual Income, and Credit Score in identifying variance?
Explain how the Central Limit Theorem (CLT) impacts the distribution of average Credit Scores from samples.
Explain how the Central Limit Theorem (CLT) impacts the distribution of average Credit Scores from samples.
In Design of Experiments, how can randomly assigning a new scoring system to customers help analyze default rates?
In Design of Experiments, how can randomly assigning a new scoring system to customers help analyze default rates?
How does the Logistic Regression formula predict the probability of customer default?
How does the Logistic Regression formula predict the probability of customer default?
Explain how the Survival Function differs from traditional probability distributions in predicting default probability.
Explain how the Survival Function differs from traditional probability distributions in predicting default probability.
How does Bayesian Statistics combine the prior belief with observed data to update estimates of the mean Credit Score for defaulters?
How does Bayesian Statistics combine the prior belief with observed data to update estimates of the mean Credit Score for defaulters?
Explain the importance of Principal Component Analysis (PCA) in reducing dimensionality for Age, Annual Income, and Credit Score variables.
Explain the importance of Principal Component Analysis (PCA) in reducing dimensionality for Age, Annual Income, and Credit Score variables.
