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The z-score is a numerical measurement that describes a value's relationship to the mean of a group of values. It is measured in terms of standard deviations from the mean. In the context of the standard normal distribution, the mean is 0, and the standard deviation is 1. Therefore, the z-score indicates how many standard deviations an element is from the mean. For example, a z-score of -2.17 signifies that the data point is 2.17 standard deviations to the left of the mean on the bell-shaped curve. This tool allows statisticians to determine how unusual or typical data points are compared to the set.

Cumulative probability refers to the probability that a random variable falls within a specified range. It measures the likelihood that a value will be less than or equal to a particular threshold. In the standard normal distribution, cumulative probability up to a given z-score represents the area under the curve to the left of that z-score.
For instance, when calculating the cumulative probability for a z-score of -2.17, you find the probability that a data point lies below this z-score. This involves finding the area under the standard normal curve from the far left up to the point where z = -2.17. Technology or a z-table often aids in these calculations by providing the cumulative probabilities directly.

The z-table, or standard normal distribution table, is a mathematical table that provides the cumulative probability of a standard normal random variable. It lists the probabilities that a z-score is less than or equal to a given value. Essentially, it shows the area under the standard normal curve to the left of a particular z-score. The z-table commonly aids in interpreting z-scores, connecting these scores to probabilities without needing complex computations.
When using a z-table, locate the row with the primary z-score value (e.g., -2.1) and the column with the second decimal place (e.g., 0.07). For z = -2.17, the table provides a probability, which is approximately 0.0150, representing the area to the left of this z-score under the curve.

Probability calculation in the context of the standard normal distribution often involves determining areas under the curve. The key to calculating probabilities is knowing that the total area under the standard normal curve sums up to 1 (or 100%).
Given a z-score like -2.17, the cumulative probability from the left up to this z-score is found first, either using a calculator or a z-table, in this case, approximately 0.0150. To find the probability or area to the right, which was the question's focus, subtract this cumulative probability from 1:\(1 - 0.0150 = 0.9850\).
Thus, 0.9850 represents the likelihood or probability that a randomly selected data point from this distribution falls to the right of the z-score -2.17.