Flashcard - Discrete Probability Distributions

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What is a discrete probability distribution?

Back

A discrete probability distribution is a statistical distribution that describes the likelihood of outcomes for a discrete random variable, which can take on a countable number of values.

Tags

CCSS.HSS.MD.A.3

CCSS.HSS.MD.A.4

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How do you calculate the mean of a discrete probability distribution?

Back

To calculate the mean, multiply each possible value by its probability and sum all the products.

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What is the expected value in probability?

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The expected value is the long-term average or mean of a random variable, calculated as the sum of all possible values, each multiplied by its probability.

Tags

CCSS.HSS.MD.A.2

Front

Define 'discrete random variable'.

Back

A discrete random variable is a variable that can take on a finite or countably infinite number of values.

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What is the probability of an event?

Back

The probability of an event is a measure of the likelihood that the event will occur, ranging from 0 (impossible) to 1 (certain).

Tags

CCSS.7.SP.C.5

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How do you find the probability of getting at least 4 correct answers on a 5-question true-false quiz?

Back

Calculate the probabilities of getting exactly 4 and exactly 5 correct answers, then sum these probabilities.

Tags

CCSS.HSS.MD.A.2

Front

What is the difference between discrete and continuous data?

Back

Discrete data consists of distinct, separate values (e.g., number of students), while continuous data can take any value within a range (e.g., height, weight).

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What is a probability mass function (PMF)?

Back

A probability mass function is a function that gives the probability that a discrete random variable is equal to a specific value.

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How do you round a number to the nearest hundredth?

Back

To round to the nearest hundredth, look at the third decimal place; if it's 5 or more, round up the second decimal place by one.

Tags

CCSS.5.NBT.A.4

Front

What is the formula for calculating the expected value of a stock?

Back

Expected Value = (Probability1 * Value1) + (Probability2 * Value2) + ... + (ProbabilityN * ValueN).

Tags

CCSS.HSS.MD.A.2