Statistics: Mean, Median, Variance, and p-values

Intro stats exam cards — central tendency, spread, sampling basics, and interpreting p-values carefully.

12 cards· by GuruOwl

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  1. 01
    What is the mean?
    The arithmetic average: sum of values divided by the number of values.
    center
  2. 02
    What is the median?
    The middle value when data are ordered (average of two middle values if even n). Robust to outliers.
    center
  3. 03
    When is the median preferred over the mean?
    When the distribution is skewed or has extreme outliers.
    center
  4. 04
    What is variance?
    Average squared deviation from the mean — measures spread. Population σ² vs sample s² (n−1).
    spread
  5. 05
    What is standard deviation?
    Square root of variance — spread in original units.
    spread
  6. 06
    What is a sampling distribution?
    The distribution of a statistic (e.g., sample mean) across repeated samples from the same population.
    inference
  7. 07
    What does the Central Limit Theorem say (informal)?
    For large enough n, the sampling distribution of the mean is approximately normal even if the population is not (finite variance).
    inference
  8. 08
    What is a p-value?
    The probability, under the null hypothesis, of seeing data as extreme as (or more extreme than) observed.
    pvalue
  9. 09
    Does p < 0.05 prove the alternative hypothesis is true?
    No — it indicates data are unlikely under the null (given assumptions); it is not the probability the null is true.
    pvalue
  10. 10
    What is a Type I error?
    Rejecting a true null hypothesis (false positive). Rate controlled by α.
    errors
  11. 11
    What is a Type II error?
    Failing to reject a false null hypothesis (false negative). Related to power (1 − β).
    errors
  12. 12
    What is a confidence interval (interpret carefully)?
    A range computed so that, in repeated sampling, a stated percentage (e.g., 95%) of such intervals would contain the true parameter — not “95% probability this interval contains it” in the frequentist sense after seeing the data.
    ci