SAT Scores Quantitative SAT scores are approximately Normally distributed with a mean of 500 and a standard deviation of 100. On the horizontal axis of the graph, indicate the SAT scores that correspond with the provided z -scores. (See the labeling in Exercise 6.14.) Answer the questions using only your knowledge of the Empirical Rule and symmetry a. Roughly what percentage of students earn quantitative SAT scores greater than 500? i. almost all ii. 75% iii. 50% iv. 25% v. about 0% b. Roughly what percentage of students earn quantitative SAT scores between 400 and 600? i. almost all ii. 95% iii. 68% iv. 34% v. about 0% c. Roughly what percentage of students earn quantitative SAT scores greater than 800? i. almost all ii. 95% iii. 68% iv. 34% v. about 0% d. Roughly what percentage of students earn quantitative SAT scores less than 200? i. almost all ii. 95% iii. 68% iv. 34% v. about 0% e. Roughly what percentage of students earn quantitative SAT scores between 300 and 700? i. almost all ii. 95% iii. 68% iv. 34% v. 2.5% f. Roughly what percentage of students earn quantitative SAT scores between 700 and 800? i. almost all ii. 95% iii. 68% iv. 34% v. 2.5%
SAT Scores Quantitative SAT scores are approximately Normally distributed with a mean of 500 and a standard deviation of 100. On the horizontal axis of the graph, indicate the SAT scores that correspond with the provided z -scores. (See the labeling in Exercise 6.14.) Answer the questions using only your knowledge of the Empirical Rule and symmetry a. Roughly what percentage of students earn quantitative SAT scores greater than 500? i. almost all ii. 75% iii. 50% iv. 25% v. about 0% b. Roughly what percentage of students earn quantitative SAT scores between 400 and 600? i. almost all ii. 95% iii. 68% iv. 34% v. about 0% c. Roughly what percentage of students earn quantitative SAT scores greater than 800? i. almost all ii. 95% iii. 68% iv. 34% v. about 0% d. Roughly what percentage of students earn quantitative SAT scores less than 200? i. almost all ii. 95% iii. 68% iv. 34% v. about 0% e. Roughly what percentage of students earn quantitative SAT scores between 300 and 700? i. almost all ii. 95% iii. 68% iv. 34% v. 2.5% f. Roughly what percentage of students earn quantitative SAT scores between 700 and 800? i. almost all ii. 95% iii. 68% iv. 34% v. 2.5%
Solution Summary: The graph represents the density curve of the Quantitative SAT score, which is normally distributed with the mean of 500 and the standard deviation of 100.
SAT Scores Quantitative SAT scores are approximately Normally distributed with a mean of 500 and a standard deviation of 100. On the horizontal axis of the graph, indicate the SAT scores that correspond with the provided
z
-scores. (See the labeling in Exercise 6.14.) Answer the questions using only your knowledge of the Empirical Rule and symmetry
a. Roughly what percentage of students earn quantitative SAT scores greater than 500?
i. almost all
ii. 75%
iii. 50%
iv. 25%
v. about 0%
b. Roughly what percentage of students earn quantitative SAT scores between 400 and 600?
i. almost all
ii. 95%
iii. 68%
iv. 34%
v. about 0%
c. Roughly what percentage of students earn quantitative SAT scores greater than 800?
i. almost all
ii. 95%
iii. 68%
iv. 34%
v. about 0%
d. Roughly what percentage of students earn quantitative SAT scores less than 200?
i. almost all
ii. 95%
iii. 68%
iv. 34%
v. about 0%
e. Roughly what percentage of students earn quantitative SAT scores between 300 and 700?
i. almost all
ii. 95%
iii. 68%
iv. 34%
v. 2.5%
f. Roughly what percentage of students earn quantitative SAT scores between 700 and 800?
i. almost all
ii. 95%
iii. 68%
iv. 34%
v. 2.5%
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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