Statistical Concepts and Inference Flashcards
7 cards from real Data Science practice questions. Tap to flip, then mark Knew It or Still Learning โ missed cards come back until you master them.
Read the first 7 Statistical Concepts and Inference flashcards as text
A 95% confidence interval for a population mean means which of the following?
Answer: If we repeated sampling many times, about 95% of such intervals would contain the true mean
A confidence level refers to the long-run proportion of constructed intervals that capture the true parameter, not the probability for a single fixed interval.
Which of the following increases the width of a confidence interval, all else equal?
Answer: Increasing the population variance
Greater population variance increases the standard error, widening the interval.
A Type I error in hypothesis testing is best described as:
Answer: Rejecting a true null hypothesis
A Type I error is a false positive: rejecting a null hypothesis that is actually true.
What does the p-value represent?
Answer: The probability of observing data at least as extreme as the sample, assuming the null is true
A p-value is the probability of results as or more extreme than observed under the assumption the null hypothesis holds.
The Central Limit Theorem states that, for a large sample size, the sampling distribution of the sample mean is approximately:
Answer: Normal regardless of population distribution
The CLT guarantees the sample mean's distribution approaches normality as sample size grows, no matter the population shape.
Statistical power is the probability of:
Answer: Rejecting the null when the alternative is actually true
Power is the probability of correctly rejecting a false null hypothesis, equal to 1 minus the Type II error rate.
Which factor does NOT increase statistical power?
Answer: Smaller significance level (alpha)
Decreasing alpha makes it harder to reject the null, which reduces power.