CAP Probability and Statistics Flashcards
Negative binomial probably distribution
A distribution that describes the odds of having a number of successful Bernoulli trials before having a given number of failures
Hypergeometric probability distribution
A function describing the probability of drawing a sample of k successes in n draws without replacement from a population with K successes and N samples
Lognormal Distribution
Any distribution whose logarithm is normally distributed
Statistics
Study of collection, analysis, interpretation, and organization of data
Cumulative Distribution Function (CDF)
A function that describes the likelihood of a random variable taking on a value less than or equal to a given value
Binomial Distribution
A function describing the number of successes in independent experiments, defined by number of trials and probability of success in each trial
Arithmetic mean
Measure of central tendency indicated by summing the sample then dividing by the sample size
Weibull probability distribution
A distribution that describes how failure rates change over time
Probability Mass Function (PMF)
A function that describes the relative likelihood of a discrete random variable taking on a given value
Harmonic mean
Measure of central tendency indicated by the reciprocal of the arithmetic mean of the reciprocals; typically used when averaging rates
normal probability distribution
A distribution shaped like a symmetric bell curve, used when sample size is large or the population standard deviation is known
Geometric mean
Measure of central tendency indicated by taking the nth root of the product of the sample; typically used when comparing items that have different properties with different ranges
Bernoulli Probability Distribution
A function where the random variable equals 1 with a probability p and equals 0 with a probability 1-p
exponential probability distribution
A function describing the amount of time that passes between events in a Poisson process
Probability Density Function (PDF)
A function that describes the relative likelihood of a continuous random variable taking on a given value