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Questions and Answers
In a probability distribution, the sum of all probabilities must equal ______.
In a probability distribution, the sum of all probabilities must equal ______.
1
In the given distributions, P(X) is the ______ of X.
In the given distributions, P(X) is the ______ of X.
probability
To find the mean of a probability distribution, you calculate the sum of ______ multiplied by their respective probabilities.
To find the mean of a probability distribution, you calculate the sum of ______ multiplied by their respective probabilities.
values
The probability of 4 out of 7 graduates getting hired follows a ______ distribution.
The probability of 4 out of 7 graduates getting hired follows a ______ distribution.
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The variance of a probability distribution measures the ______ of the distribution around the mean.
The variance of a probability distribution measures the ______ of the distribution around the mean.
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Study Notes
Probability Distributions
- A probability distribution is a function that describes the likelihood of obtaining different possible outcomes in an experiment
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Key properties of a probability distribution:
- The probabilities of all possible outcomes must add up to 1
- The probabilities must be between 0 and 1
Determining Probability Distributions
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Question One a):
- The probabilities for all the outcomes of X add up to 1, so the table represents a probability distribution.
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Question One b):
- The probabilities for all the outcomes of X add up to 1, so the table represents a probability distribution.
Mean, Variance, and Standard Deviation
- The mean of a discrete probability distribution is the average value of the random variable, weighted by the probabilities of each value
- The variance measures the spread of the distribution. It is the average of the squared deviations from the mean
- The standard deviation is the square root of the variance, indicating the average distance from the mean.
Finding Mean, Variance, and Standard Deviation
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Question Two:
- To find the mean: Multiply each possible outcome by its probability, and sum the results
- To find the variance: Multiply each outcome's probability by the square of the difference between the outcome and the mean, and sum the results
- To find the standard deviation: Take the square root of the variance
The Binomial Probability Distribution
- The binomial distribution is a probability distribution that describes the probability of obtaining a specific number of successes in a sequence of independent trials.
- The trials must have exactly two possible outcomes: success or failure.
- The likelihood of success (p) should remain constant over all the trials.
Finding The Probability of Success
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Question Three:
- The probability of success (p) is 75%
- The probability of failure (q) is 25%
- There are 7 trials (n)
- We need to find the probability of exactly 4 successes (x)
- The formula to calculate this probability is:
(n choose x) * (p^x) * (q^(n-x))
- Where (n choose x) is the binomial coefficient calculated as (n!)/ (x! * (n-x)!)
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Description
Test your understanding of probability distributions, including their key properties, mean, variance, and standard deviation. This quiz will challenge you to apply concepts and determine probability distributions in different scenarios.