Statistics concepts, explained
- What is the difference between a t-test and a z-test?
Learn the key differences between a t-test and a z-test, including when to use each based on sample size and population standard deviation.
- What Does Correlation Not Tell You?
Correlation measures the strength of a relationship between two variables, but it cannot tell you if one variable causes the other to change.
- What is a p-value, in plain terms?
A p-value measures the probability of seeing your data by random chance if the null hypothesis is true, helping you decide if your results are significant.
- How do you read a confidence interval?
Learn how to interpret a confidence interval, understand the margin of error, and avoid common pitfalls when reading statistical estimates.
- How do you use a z-score?
Learn what a z-score is, how to calculate it, and how it helps you find probabilities and compare different datasets in statistics.
- What is a binomial distribution?
A binomial distribution is a statistical probability model that calculates the chances of getting a specific number of successes in a fixed number of trials.
- How does conditional probability work?
Conditional probability calculates the likelihood of an event occurring given that another event has already happened, effectively shrinking the sample space.
- What is the difference between independent and mutually exclusive events?
Understand the key differences between independent events (which don't affect each other) and mutually exclusive events (which cannot happen together).
- How do you read a box plot?
Learn how to read a box plot, identify the median, quartiles, and outliers, and understand what this visual tool tells you about your data spread.
- What is the difference between mean, median and mode, and when does each matter?
Learn the difference between mean, median, and mode, and how to choose the right measure of central tendency for your statistics homework.
- What does standard deviation tell you?
Standard deviation measures how spread out the numbers in a data set are around the mean, helping you understand the variation in your data.