Normal Distribution of Test Scores: Percentages for Various Ranges

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SUMMARY

The discussion centers on the normal distribution of test scores, specifically with a mean (μ) of 100 and a standard deviation (σ) of 15. Participants seek to determine the percentage of the population that falls within specific score ranges, such as between 100 and 125, and above 132. The normal distribution, also known as the Gaussian distribution, is characterized by its bell curve shape and is defined mathematically by a specific equation. The total area under the curve equals 1, indicating that the probability of obtaining any score is certain.

PREREQUISITES
  • Understanding of normal distribution concepts
  • Familiarity with mean (μ) and standard deviation (σ)
  • Knowledge of Gaussian integrals
  • Basic calculus for integration
NEXT STEPS
  • Study the properties of the Gaussian distribution
  • Learn how to use Z-scores for normal distribution calculations
  • Explore Gaussian integral tables for probability calculations
  • Practice calculating percentages of populations within normal distribution ranges
USEFUL FOR

Students, statisticians, educators, and anyone involved in data analysis or assessment who seeks to understand the implications of normal distribution on test scores.

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Scores on a particular test are normally distributed in the population, with a mean of 100 and a standard deviation of 15. What percentage of the population have scores ...

a) Between 100 and 125

b) Between 82 and 106

c) Between 110 and 132

d) Above 132

e) Equal to 132
HELP ME UNDERSTAND THIS PLEASE!
 
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THe normal distribution is also know as the Gaussian distribution or a "bell curve" It is described by the equation on the wikipedia page. For your problem
mu = location of the peak probability = 100
sigma^2 = variance = standard variation = 15

You may notice the part of the equation outside the exponential. This is called a normalizing factor. This factor adusts the height of the function depending on the value of sigma so the TOTAL area under the curve is 1. THis means if you the take the test, the probaility that you have any score is 1.

The probability of getting some score between two values is simply the integral of the curve between these two scores. However, it's usless trying to actually do the integral. You need to look up the gaussian integrals in a table.
 

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