Find the area of the shaded region. The graph to the right depicts IQ scores of adults and those scores are normally distributed with a mean of 100 and a standard deviation of 15 The area of the shaded region is
Find the area of the shaded region. The graph to the right depicts IQ scores of adults and those scores are normally distributed with a mean of 100 and a standard deviation of 15 The area of the shaded region is
Find the area of the shaded region. The graph to the right depicts IQ scores of adults and those scores are normally distributed with a mean of 100 and a standard deviation of 15 The area of the shaded region is
Find the area of the shaded region. The graph to the right depicts IQ scores of adults and those scores are normally distributed with a mean of 100 and a standard deviation of 15
The area of the shaded region is
Transcribed Image Text:The image depicts a normal distribution curve, also known as a bell curve, commonly used in statistics. The curve is symmetrical around the mean and gradually tapers off at both ends.
In this particular graph:
- The x-axis is marked with values, specifically at 90 and 120, which likely represent data points or scores within a dataset.
- The area between 90 and 120 is shaded, indicating the range of values considered for a specific calculation, such as probability, percentage, or standard deviation within this distribution.
- The shaded region under the curve represents the probability or proportion of observations falling within this interval.
This type of graph is typically used to illustrate how data is distributed around the mean and to analyze probabilities, standard deviations, and variations in datasets.
Features Features Normal distribution is characterized by two parameters, mean (µ) and standard deviation (σ). When graphed, the mean represents the center of the bell curve and the graph is perfectly symmetric about the center. The mean, median, and mode are all equal for a normal distribution. The standard deviation measures the data's spread from the center. The higher the standard deviation, the more the data is spread out and the flatter the bell curve looks. Variance is another commonly used measure of the spread of the distribution and is equal to the square of the standard deviation.
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