Data Science Statistical Concepts and Inference Questions and Answers Flashcards

A machine learning model yields a p-value of 0.03 when testing whether a new feature improves prediction accuracy. With alpha = 0.01, what is the correct conclusion?

Answer: Fail to reject the null hypothesis because 0.03 > 0.01

Since the p-value of 0.03 exceeds the significance level of 0.01, we do not have sufficient evidence to reject the null hypothesis at that threshold.

What does the Central Limit Theorem guarantee about the sampling distribution of the sample mean?

Answer: It approaches a normal distribution as sample size increases, regardless of population shape

The Central Limit Theorem states that the distribution of sample means approaches normality as sample size grows, even if the underlying population is non-normal.

In Bayesian inference, what role does the prior distribution play?

Answer: It encodes beliefs about a parameter before observing data

The prior distribution in Bayesian inference captures existing knowledge or beliefs about a parameter before any new data is collected.

A correlation coefficient of r = -0.92 between two variables indicates which of the following?

Answer: A strong negative linear relationship

An r value of -0.92 indicates a strong negative linear association, meaning as one variable increases the other tends to decrease substantially.

Which resampling technique estimates the variability of a statistic by repeatedly sampling with replacement from the observed data?

Answer: Bootstrap

The bootstrap method draws repeated samples with replacement from the original dataset to estimate the sampling distribution of a statistic.

When is the chi-squared test of independence most appropriate?

Answer: Testing whether two categorical variables are associated

The chi-squared test of independence evaluates whether there is a statistically significant association between two categorical variables in a contingency table.