Multiple ComparisonsDependent Variable: Sessions Tukey HSD (I) Group(J) GroupMean Difference (I-J)Std. ErrorSig.95% Confidence IntervalLower BoundUpper Bound1.002.00-2.33333.97996.109-5.2194.55273.00-5.91667*.91667<.001-8.6163-3.21702.001.002.33333.97996.109-.55275.21943.00-3.58333*.91667.014-6.2830-.88373.001.005.91667*.91667<.0013.21708.61632.003.58333*.91667.014.88376.2830 *. The mean difference is significant at the 0.05 level. Question Why do researchers compute Tukey HSD tests? Between which two groups is there a statically significant difference? If a researcher fails to reject the null hypothesis for the ANOVA f test, should she conduct Tukey HSD tests?

It is defined as the post hoc test in that the comparisons between variables are made after the data has already been collected. This differs from an a priori test, in which these comparisons are made in advance. (a) The researchers would prefer Tuskey HSD test because it is known as a statistical tool used to determine if the relationship between two sets of data is statistically significant – that is, whether there's a strong chance that an observed numerical change in one value is causally related to an observed change in another value. In other words, the Tukey test is a way to test an experimental hypothesis. (b) The statistical difference is between independent group t - test and paired test. Independent Group t-test: The Independent Group t-test is designed to compare means between two groups where there are different subjects in each group. Ideally, these subjects are randomly selected from a larger population of subjects and assigned to one of two treatments. Another way to assign subjects to two groups is to randomly assign them to one of two treatments at the time they enter a study. This randomization is often performed in a double-blind fashion. Paired test : The two groups are the same or matched. That is, the same subjects are observed twice, often with some intervention taking place between measures. One advantage of using the same subjects is that experimental variability if less than for the independent group case. For this test the mean difference between the two repeated observations is observed and compared. If the difference is sufficiently great then there is evidence that the treatment caused some change in the observed variable. (c) Yes she should conduct Tukey HSD tests.

Answered: iple Comparisons Dependent Variable:…

Computer Networking: A Top-Down Approach (7th Edition)

7th Edition

ISBN:9780133594140

Author:James Kurose, Keith Ross

Publisher:James Kurose, Keith Ross

Chapter1: Computer Networks And The Internet

Section: Chapter Questions

Problem R1RQ: What is the difference between a host and an end system? List several different types of end...

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Related questions

Question

Multiple Comparisons
Dependent Variable: Sessions
Tukey HSD
(I) Group	(J) Group	Mean Difference (I-J)	Std. Error	Sig.	95% Confidence Interval
Lower Bound	Upper Bound
1.00	2.00	-2.33333	.97996	.109	-5.2194	.5527
3.00	-5.91667^*	.91667	<.001	-8.6163	-3.2170
2.00	1.00	2.33333	.97996	.109	-.5527	5.2194
3.00	-3.58333^*	.91667	.014	-6.2830	-.8837
3.00	1.00	5.91667^*	.91667	<.001	3.2170	8.6163
2.00	3.58333^*	.91667	.014	.8837	6.2830

*. The mean difference is significant at the 0.05 level.

Question
Why do researchers compute Tukey HSD tests?
Between which two groups is there a statically significant difference?
If a researcher fails to reject the null hypothesis for the ANOVA f test, should she conduct Tukey HSD tests?