#4.2A study was done on proctored and nonproctored tests. The results are shown in the table. Assume that the two samples are independent simple random samples selected from normally distributed populations, and do not assume that the population standard deviations are equal. Protorednonproctoreduu1u2n3431x overbar 75.1782.06s11.0118.33test statisticP-Valueconclusion of testconstruct a confidence interval suitable for testing the claim that students taking nonprotored tests get higher mean score than those taking proctored tests does confidence interval support conclusion

Name: #4.2A study was done on proctored and nonproctored tests. The results
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Description: #4.2A study was done on proctored and nonproctored tests. The results are shown in the table. Assume that the two samples are independent simple random samples selected from normally distributed populations, and do not assume that the population sta

GivenLevel of significance = 0.01Null Hypothesis : µ1 = µ2 Alternative Hypothesis : µ1 < µ2Degree…

Answered: #4.2 A study was done on proctored and…

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#4.2

A study was done on proctored and nonproctored tests. The results are shown in the table. Assume that the two samples are independent simple random samples selected from normally distributed populations, and do not assume that the population standard deviations are equal.

	Protored	nonproctored
u	u1	u2
n	34	31
x overbar	75.17	82.06
s	11.01	18.33

test statistic

P-Value

conclusion of test

construct a confidence interval suitable for testing the claim that students taking nonprotored tests get higher mean score than those taking proctored tests

does confidence interval support conclusion

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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