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Changes for page b. Test

Last modified by Demi Breen on 2023/04/09 15:10
From version 22.1
edited by Demi Breen
on 2023/03/28 12:22
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To version 26.1
edited by Hugo van Dijk
on 2023/03/30 15:16
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110 110  
111 111  = 3. Results =
112 112  
113 +Firstly, the Jarque-Bera test [2] was used to check for normality. When the answers for 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.
113 113  
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116 +Even though the mean rejections were higher for emotion-based (0,875) than for goal-based(0,125). This difference was not significant.
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118 +Furthermore, there was no significant difference in questionnaire answers between the two groups.
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120 +The table below shows the p-value per measure.
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114 114  = 4. Discussion =
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117 117  = 5. Conclusions =
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119 119  
129 +== References ==
130 +
120 120  [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]]
132 +
133 +[2] Thorsten Thadewald and Herbert Büning. “Jarque–Bera test and its competitors for testing
134 +normality–a power comparison”. In: Journal of applied statistics 34.1 (2007), pp. 87–105.
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136 +
137 +[3] Nadim Nachar et al. “The Mann-Whitney U: A test for assessing whether two indepen-
138 +dent samples come from the same distribution”. In: Tutorials in quantitative Methods for
139 +Psychology 4.1 (2008), pp. 13–20.
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141 +
142 +[4] Tae Kyun Kim. “T test as a parametric statistic”. In: Korean journal of anesthesiology 68.6
143 +(2015), pp. 540–546.
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