Here are the essential concepts you must grasp in order to answer the question correctly.
Standard Normal Distribution
The standard normal distribution is a special case of the normal distribution where the mean is 0 and the standard deviation is 1. It is represented by the variable Z, which allows for the calculation of probabilities and percentiles for any normal distribution by standardizing values. This distribution is symmetric and bell-shaped, making it a fundamental concept in statistics for understanding how data is distributed.
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Z-Score
A Z-score is a statistical measurement that describes a value's relationship to the mean of a group of values. It is calculated by subtracting the mean from the value and then dividing by the standard deviation. A Z-score indicates how many standard deviations an element is from the mean, allowing for comparison across different datasets and facilitating the use of the standard normal distribution for probability calculations.
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Cumulative Probability
Cumulative probability refers to the probability that a random variable takes on a value less than or equal to a specific value. In the context of the standard normal distribution, it is represented by the area under the curve to the left of a given Z-score. This concept is crucial for finding probabilities associated with specific Z-scores, such as P(z < 1.28), which can be determined using standard normal distribution tables or technology.
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