A math teacher claims that she has developed a review course that increases the scores of students on the math portion of a college entrance exam. Based on data from the administrator of the exam, scores are normally distributed with μ=516.The teacher obtains a random sample of 2200 students, puts them through the review class, and finds that the mean math score of the 2200 students is 521 with a standard deviation of 116. Complete parts (a) through (d) below. A math teacher claims that she has developed a review course that increases the scores of students on the math portion of a college entrance exam. Based on datafrom the administrator of the exam, scores are normally distributed with u= 516. The teacher obtains a random sample of 2200 students, puts them through the reviewclass, and finds that the mean math score of the 2200 students is 521 with a standard deviation of 116. Complete parts (a) through (d) below.(c) Do you think that a mean math score of 521 versus 516 will affect the decision of a school admissions administrator? In other words, does the increase in the scorehave any practical significance?Yes, because every increase in score is practically significant.No, because the score became only 0.97% greater.(d) Test the hypothesis at the a = 0.10 level of significance with n = 350 students. Assume that the sample mean is still 521 and the sample standard deviation is still116. Is a sample mean of 521 significantly more than 516? Conduct a hypothesis test using the P-value approach.Find the test statistic.to(Round to two decimal places as needed.)Find the P-value.The P-value is(Round to three decimal places as needed.)ARost Is the sample mean statistically significantly higher?NoYesWhat do you conclude about the impact of large samples on the P-value?A. As n increases, the likelihood of not rejecting the null hypothesis increases. However, large samples tend to overemphasize practically insignificantdifferences.B. As n increases, the likelihood of rejecting the null hypothesis increases. However, large samples tend to overemphasize practically insignificant differences.C. As n increases, the likelihood of not rejecting the null hypothesis increases. However, large samples tend to overemphasize practically significant differences.D. As n increases, the likelihood of rejecting the null hypothesis increases. However, large samples tend to overemphasize practically significant differences.

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MATLAB: An Introduction with Applications

6th Edition

ISBN:9781119256830

Author:Amos Gilat

Publisher:Amos Gilat

Chapter1: Starting With Matlab

Section: Chapter Questions

Problem 1P

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A math teacher claims that she has developed a review course that increases the scores of students on the math portion of a college entrance exam. Based on data from the administrator of the exam, scores are normally distributed with μ=516.The teacher obtains a random sample of 2200 students, puts them through the review class, and finds that the mean math score of the 2200 students is 521 with a standard deviation of 116. Complete parts (a) through (d) below.

Is the sample mean statistically significantly higher?
No
Yes
What do you conclude about the impact of large samples on the P-value?
A. As n increases, the likelihood of not rejecting the null hypothesis increases. However, large samples tend to overemphasize practically insignificant
differences.
B. As n increases, the likelihood of rejecting the null hypothesis increases. However, large samples tend to overemphasize practically insignificant differences.
C. As n increases, the likelihood of not rejecting the null hypothesis increases. However, large samples tend to overemphasize practically significant differences.
D. As n increases, the likelihood of rejecting the null hypothesis increases. However, large samples tend to overemphasize practically significant differences.

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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