Suppose the distribution of scores of 1000 students who take a standardized intelligence test is a normal distribution. Also suppose that the distributions mean is 450 and it’s standard deviation is 35.A) how many scores do we expect to fall between 345 and 555?B) how many scores do we expect to fall below 345?(Round to the nearest whole number as needed) Section 14.4- The Normal DistributionThe normal distribution (normal curve) is a way to study data using the information you.ave learned about. A normal distribution is a bell shaped curve that is symmetric withrespect to the mean. A normal distribution usually applies to a whole population, not asample, therefore the mean is now called u (mu).)34%34%8115✓2.35%-30-35D13.5%-20-10-250-150m68%95%99.7%13.5%+10SD+202.35%+30SD

Given: n = 1000 μ = 450 σ = 35

Answered: Suppose the distribution of scores of…

MATLAB: An Introduction with Applications

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ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

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Suppose the distribution of scores of 1000 students who take a standardized intelligence test is a normal distribution. Also suppose that the distributions mean is 450 and it’s standard deviation is 35. A) how many scores do we expect to fall between 345 and 555? B) how many scores do we expect to fall below 345? (Round to the nearest whole number as needed)

Section 14.4- The Normal Distribution
The normal distribution (normal curve) is a way to study data using the information you
.ave learned about. A normal distribution is a bell shaped curve that is symmetric with
respect to the mean. A normal distribution usually applies to a whole population, not a
sample, therefore the mean is now called u (mu).)
34%
34%
8
115
✓
2.35%
-30
-35D
13.5%
-20
-10
-250-150
m
68%
95%
99.7%
13.5%
+10
SD
+20
2.35%
+30
SD

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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