Females' SAT Scores (Example 8) According to the College Board, the mean quantitative SAT score for female college-bound high school seniors in 2012 was 500. SAT scores are approximately Normally distributed with a population standard deviation of 100. A scholarship committee wants to give awards to college-bound women who score at the 96th percentile or above on the SAT. What score does an applicant need? Include a well-labeled Normal curve as part of your answer. See page 299 for guidance.
Females' SAT Scores (Example 8) According to the College Board, the mean quantitative SAT score for female college-bound high school seniors in 2012 was 500. SAT scores are approximately Normally distributed with a population standard deviation of 100. A scholarship committee wants to give awards to college-bound women who score at the 96th percentile or above on the SAT. What score does an applicant need? Include a well-labeled Normal curve as part of your answer. See page 299 for guidance.
Solution Summary: The author explains how to determine the SAT score needed by an applicant to be at 96th percentile or above to get an award and includes the well-labeled normal curve.
Females' SAT Scores (Example 8) According to the College Board, the mean quantitative SAT score for female college-bound high school seniors in 2012 was 500. SAT scores are approximately Normally distributed with a population standard deviation of 100. A scholarship committee wants to give awards to college-bound women who score at the 96th percentile or above on the SAT. What score does an applicant need? Include a well-labeled Normal curve as part of your answer. See page 299 for guidance.
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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