The scores on a college entrance exam have an approximate normal distribution with mean, μ = 52 points and a standard deviation, σ = 11 points. a. About 68% of they values lie between what two values? These values are ________________. The z-scores are respectively. b. About 95% of they values lie between what two values? These values are ________________ The z-scores are respectively. c. About 99.7% of the y values lie between what two values? These values are ________________. The z-scores are_________respectlvely.
The scores on a college entrance exam have an approximate normal distribution with mean, μ = 52 points and a standard deviation, σ = 11 points. a. About 68% of they values lie between what two values? These values are ________________. The z-scores are respectively. b. About 95% of they values lie between what two values? These values are ________________ The z-scores are respectively. c. About 99.7% of the y values lie between what two values? These values are ________________. The z-scores are_________respectlvely.
The scores on a college entrance exam have an approximate normal distribution with mean,
μ
=
52
points and a standard deviation,
σ
=
11
points.
a. About 68% of they values lie between what two values? These values are ________________. The z-scores are respectively.
b. About 95% of they values lie between what two values? These values are ________________ The z-scores are respectively.
c. About 99.7% of the y values lie between what two values? These values are ________________. The z-scores
are_________respectlvely.
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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