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Changes for page b. Test

Last modified by Demi Breen on 2023/04/09 15:10
From version 40.1
edited by Maya Elasmar
on 2023/04/03 13:16
Change comment: There is no comment for this version
To version 42.1
edited by Maya Elasmar
on 2023/04/03 13:28
Change comment: There is no comment for this version

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61 61  In an optimal scenario where we can test the robot on PwD. We would have measured the number of times a person went out. We would also have measured the effect of the goal and emotion-based motivation on the long-term over the people. Whether it will be less effective over time or not. We would also measure the emotional effect on the caregivers and the functional effect. By the functional effect, we mean whether they indeed have more time to do other tasks or not. It would also have been perfect if we could measure the effect of the walks on the PwD and their health.
62 62  
63 -The questionnaire for the feedback is in the attachment (Questionnaire (2)). The questionnaire is based on a questionnaire in the paper " Measuring acceptance of an assistive social robot: a suggested toolkit " [5]. There are also 5 question at the end that we added ourselves, because we think it fits our experiment.
63 +The questionnaire for the feedback is in the attachment (Questionnaire (2)). The questionnaire is based on a questionnaire in the paper " Measuring acceptance of an assistive social robot: a suggested toolkit " [2]. There are also 5 question at the end that we added ourselves, because we think it fits our experiment.
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65 65  The questionnaire measures the experiment of the interaction of the students with the robot. By that we mean it measures:
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121 121  === ANOVA ===
122 122  
123 -Firstly, the Jarque-Bera test [2] was used to check for normality. When the answers to a question weren't normally distributed, the Mann-Whitney U-Test [3] was used. For normally distributed answers, the T-Test [4] was used. These tests used the null hypothesis that there is no significant difference between the two groups. When the calculated probability value (p-value) is less than 0.05, we can reject the null hypothesis and conclude that there is a significant difference between the two groups for the answers to that question.
123 +Firstly, the Jarque-Bera test [3] was used to check for normality. When the answers to a question weren't normally distributed, the Mann-Whitney U-Test [4] was used. For normally distributed answers, the T-Test [5] was used. These tests used the null hypothesis that there is no significant difference between the two groups. When the calculated probability value (p-value) is less than 0.05, we can reject the null hypothesis and conclude that there is a significant difference between the two groups for the answers to that question.
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125 125  Even though the average rejections were higher for emotion-based (0,875) than for goal-based(0,125). This difference was not significant.
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182 182  [1] Brysbaert, M. (2019). How many participants do we have to include in properly powered experiments? A tutorial of power analysis with reference tables. //Journal of Cognition//, //2//(1), 16. DOI: [[http:~~/~~/doi.org/10.5334/joc.72>>url:http://doi.org/10.5334/joc.72]]
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184 -[2] Thorsten Thadewald and Herbert Büning. “Jarque–Bera test and its competitors for testing
184 +[2] M. Heerink, B. Kröse, V. Evers, and B. Wielinga, “Measuring acceptance of an assistive social robot: a suggested toolkit .” [Online]. Available: https:~/~/mheerink.home.xs4all.nl/pdf/HeerinkRo-man09.pdf.
185 +
186 +[3] Thorsten Thadewald and Herbert Büning. “Jarque–Bera test and its competitors for testing
185 185  normality–a power comparison”. In: Journal of applied statistics 34.1 (2007), pp. 87–105.
186 186  
187 -[3] Nadim Nachar et al. “The Mann-Whitney U: A test for assessing whether two indepen-
189 +[4] Nadim Nachar et al. “The Mann-Whitney U: A test for assessing whether two indepen-
188 188  dent samples come from the same distribution”. In: Tutorials in quantitative Methods for
189 189  Psychology 4.1 (2008), pp. 13–20.
190 190  
191 -[4] Tae Kyun Kim. “T test as a parametric statistic”. In: Korean journal of anesthesiology 68.6
193 +[5] Tae Kyun Kim. “T test as a parametric statistic”. In: Korean journal of anesthesiology 68.6
192 192  (2015), pp. 540–546.
193 193  
194 -[5] M. Heerink, B. Kröse, V. Evers, and B. Wielinga, “Measuring acceptance of an assistive social robot: a suggested toolkit .” [Online]. Available: https:~/~/mheerink.home.xs4all.nl/pdf/HeerinkRo-man09.pdf.
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