Stats Part 4 Flashcards
(22 cards)
What is Bayesian inference?
A method of updating beliefs about a parameter using Bayes’ theorem.
What is a prior distribution?
The probability distribution representing beliefs before observing data.
What is a posterior distribution?
The updated belief distribution after seeing the data.
What is a credible interval?
The Bayesian equivalent of a confidence interval — a range with a specified probability of containing the parameter.
How is Bayesian inference different from frequentist inference?
Bayesian uses prior beliefs and updates them; frequentist relies solely on sample data.
What is the Poisson distribution used for?
Modeling the number of events in a fixed interval of time or space.
What is the exponential distribution?
A continuous distribution describing time between Poisson events.
What is the uniform distribution?
A distribution where all outcomes are equally likely.
What is the t-distribution?
A bell-shaped distribution used instead of normal when sample sizes are small.
What is the chi-square distribution?
A distribution of squared standard normal variables, used in variance-related tests.
What is the mean?
The arithmetic average of a set of values.
What is the median?
The middle value of a sorted dataset.
What is the mode?
The most frequently occurring value in a dataset.
What is variance?
The average of squared deviations from the mean.
What is standard deviation?
The square root of the variance.
What is a z-score?
A standardized value indicating how many standard deviations a data point is from the mean.
How do you calculate a z-score?
Subtract the mean and divide by the standard deviation: z = (x - μ) / σ.
What does a z-score of 0 mean?
The value is equal to the mean.
Why is statistical significance not the same as practical significance?
A result can be statistically detectable but have minimal real-world impact.
What is p-hacking?
Manipulating data or analyses to obtain statistically significant results.
What is the replication crisis?
Widespread failure to reproduce results in scientific studies due to poor practices or chance findings.
Why is it important to pre-register hypotheses?
To prevent cherry-picking results and ensure scientific integrity.
