Do students perform worse when they take an exam alone than when they take an exam in a classroom setting? Eight students were given two tests of equal difficulty. They took one test in a solitary room and they took the other in a room filled with other students. The results are shown below. Exam Scores Alone 63 76 88 77 83 80 76 86 Classroom 62 82 93 87 84 81 82 93 Assume a Normal distribution. What can be concluded at the the αα = 0.10 level of significance level of significance? Based on this, we should the null hypothesis. Thus, the final conclusion is that ... The results are statistically insignificant at αα = 0.10, so there is statistically significant evidence to conclude that the population mean test score taking the exam alone is equal to the population mean test score taking the exam in a classroom setting. The results are statistically insignificant at αα = 0.10, so there is insufficient evidence to conclude that the population mean test score taking the exam alone is less than the population mean test score taking the exam in a classroom setting. The results are statistically significant at αα = 0.10, so there is sufficient evidence to conclude that the eight students scored lower on average taking the exam alone compared to the classroom setting. The results are statistically significant at αα = 0.10, so there is sufficient evidence to conclude that the population mean test score taking the exam alone is less than the population mean test score taking the exam in a classroom setting.

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Description: Do students perform worse when they take an exam alone than when they take an exam in a classroom setting? Eight students were given two tests of equal difficulty. They took one test in a solitary room and they took the other in a room filled with ot

Glencoe Algebra 1, Student Edition, 9780079039897, 0079039898, 2018

18th Edition

ISBN:9780079039897

Author:Carter

Publisher:Carter

Chapter10: Statistics

Section10.4: Distributions Of Data

Problem 19PFA

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Do students perform worse when they take an exam alone than when they take an exam in a classroom setting? Eight students were given two tests of equal difficulty. They took one test in a solitary room and they took the other in a room filled with other students. The results are shown below.

Exam Scores

Alone	63	76	88	77	83	80	76	86
Classroom	62	82	93	87	84	81	82	93

Assume a Normal distribution. What can be concluded at the the αα = 0.10 level of significance level of significance?

Based on this, we should the null hypothesis.
Thus, the final conclusion is that ...
- The results are statistically insignificant at αα = 0.10, so there is statistically significant evidence to conclude that the population mean test score taking the exam alone is equal to the population mean test score taking the exam in a classroom setting.
- The results are statistically insignificant at αα = 0.10, so there is insufficient evidence to conclude that the population mean test score taking the exam alone is less than the population mean test score taking the exam in a classroom setting.
- The results are statistically significant at αα = 0.10, so there is sufficient evidence to conclude that the eight students scored lower on average taking the exam alone compared to the classroom setting.
- The results are statistically significant at αα = 0.10, so there is sufficient evidence to conclude that the population mean test score taking the exam alone is less than the population mean test score taking the exam in a classroom setting.

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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